System and Method to Process and Display Information Related to Real Estate by Developing and Presenting a Photogrammetric Reality Mesh

ABSTRACT

Systems and methods are disclosed for multidimensional visualization of data and using the visualization in any of a number of applications to result in visualization configurations usable for a variety of purposes. The system includes one or more processors, one or more databases, at least one graphical user interface (GUI), and control technology for a user to control a display, where the display typically is visualizable through the GUI.

This application is a National Stage application claiming priority toPCT Application No. PCT/US2021/065618 filed on Dec. 30, 2021, whichclaims priority to U.S. patent application Ser. No. 17/565,108 filed onDec. 29, 2021, all of which claims priority to U.S. Provisional PatentApplication No. 63/199,458, filed Dec. 30, 2020, the entirety of whichis incorporated by reference.

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

BACKGROUND OF THE PRESENT INVENTION

At present, determining attributes of a particular living or commercialunit is both labor intensive and unreliable. A user needs to arduouslylook up details about a unit of interest and, for example, in order todetermine a fair market value for the unit, a user must properly comparedozens of attributes across many parameters to make that decision. Forexample, what is the general value of a neighborhood or submarket? Howdo the number of bedrooms or bathrooms influence price? What fixturesare in a unit and how does that influence price? Are there issues withthe building itself, such as a rat problem? Is there pending litigationabout the building? What were previous sale prices? How much of abuilding consists of rental units? How does the location of theapartment within a building influence its price? Is the present ownercurrent on taxes? If I make selected changes to my unit, how do thosechanges influence market value?

When all data is obtained, algorithms can be used for pricing. However,the data changes often, seemingly hourly for a particular area orbuilding, so obtaining real time fair pricing (in one example) can bearduous or impossible.

The present invention is intended to overcome this issue by streamliningand automating the data collection and analysis process, allowing usersto make selections of parameters, and the present invention uses anaugmented reality approach to forming and utilizing a visualization ofan area, a building, or even an apartment.

BRIEF DESCRIPTION OF THE PRESENT INVENTION

The present invention is directed to systems and methods formultidimensional visualization of data and using the visualization inany of a number of applications to result in visualizationconfigurations usable for a variety of purposes. The system includes oneor more processors, one or more databases, at least one graphical userinterface (GUI), and control technology for a user to control a display,where the display typically is visualizable through the GUI. Theprocessor(s) of the present invention may include engines for performingselect functions, such as for processing certain data or certain typesof data. In addition or alternatively, the processor(s) of the presentinvention may be pre-programmed to perform such functions. In oneexample of the present invention, data regarding a particular buildingin a particular locale can be used to configure a two-, three-, ormulti-dimensional visual array of the building, including fixtures andappliances, which can be used (1) in comparison to other buildings (suchas in the neighborhood), unit-by-unit, (2) including additionaldimensions of data, such as pricing, (3) to determine a comparative fairvalue for the building or unit, or (4) other desired results asidentified herein below. In at least some embodiments, the value and/orother parameters can be determined automatically, with users affordedthe opportunity for additional or alternative parameter selection.

That is, the present invention amasses data from numerous public andprivate sources, does so on an ongoing basis, and uses the data tocreate multi-layered visualizations, typically using augmented realityand/or 3D image texture mapping (reality mesh), and uses color-coding,shading, fogging, and highlighting, included automatically by a systemprocessor processing data, and user adjustable parameters, to conveydetailed information about a geography, where the data is used to drawconclusions and formulate trends.

A primary goal of the approach of the present invention is to create areality or augmented reality mesh visualization of a particulargeography which can be used for any of a variety of purposes, at leastsome of which may be concurrent, many of which are described herein.This geography may be selectable as broadly as an entire city or stateor as narrowly as a portion of a single building. The selected area canbe considered an augmented reality mesh. This reality mesh is anaugmented reality type of visual depiction of a particular geographicarea, neighborhood, or real estate submarket which can be furtheraugmented based on attributes, such as those of particular interest to aparticular user. In the present invention, with a Graphical UserInterface (GUI), the reality mesh can be displayed, interacted with, andacted upon by a user or automatically.

The reality mesh of the present invention is a 3D computer filepotentially executable and containing metadata for uses such as but notlimited to control, created through photogrammetric processing of manyaerial images of a geography area usable to generate a virtualrepresentation in 3D. Reality mesh files can be viewed with a GeographicInformation System (GIS), such as virtual globe software like GoogleEarth and positioned in-situ to match a two-dimensional map. This servesto augment the geographic details with vertical extrusions and helpunderstand a city, sub-market, neighborhood, city block, or building. Aproblem encountered by the real estate industry is that reality meshfiles before this invention do not contain any metadata about the legalproperties they contain and can provide no additional insights beyondaesthetics. The present invention solves this gap by formulating a datamodel for a relational database, corresponding to the reality mesh,augmentable as the data are collected and stored, where the data includedata regarding a variety of attributes of each property, unit, or realestate market or submarket, and includes a user interface for displayingselected attributes of the property both in an augmented reality senseas well as being further selectable. The attributes may be userselectable or processor selectable or both, and may include the user'sability to expand or contract the geography of view, including selectingthe area of interest across three dimensions. The database of thepresent invention is configured for on-going adjustment based onintroduction of new data and new data sources, and is further configuredfor rapid delivery of selected content. Rapid delivery is importantbecause of the large file sizes of high-resolution reality mesh files.The database of the present invention is further created by normalizingreceived data to allow for this rapid turnaround.

In another example, sales or rental data can be used to highlightresidential (or commercial) units which show pricing in certain ranges(such as using differentiated colors by range) or time frames of salesor both so as to provide fair market estimates for a particular propertyand can do so relative to other properties. In other words, a personwith graphical user interface access and a need can see or determine howto price or improve pricing for a property, or understand market forcesin general.

A reality mesh more generally, also known as a photogrammetric model, isa precisely scaled, high-resolution image texture-mapped model of ageographic area. Typically one or more images are captured by aircraftor spacecraft and processed with sophisticated photogrammetry softwarethat outputs a homogenous polygon model that can be viewed using aGraphical User Interface (GUI) using a Geographic Information System(GIS) or 3D model viewing software such as a mainstream web browser thatsupports common 3D graphic file display standards such as WebGL. Realitymesh models can be prepared with varying degrees of resolution andfidelity. An objective when creating a reality mesh is to find a balancebetween image quality and file size to maximize system performance whileconsidering the delivery method, such as web (low fidelity) ortraditional local desktop GIS (high fidelity). In the system of thepresent invention's modeling of Manhattan, as an example, the systemuses a 2 cm resolution reality mesh, which is extremely detailed andperforms adequately in web delivered applications. This level of detailis advantageous over prior art in being able to both (1) display in anaugmented reality way (thereby providing life-like information to aviewer) and (2) overlay the display with content such as informativecoloring, highlighting, and/or text with precision to the actualsubmarkets, properties, building floors or building architecturalelements embedded within the reality mesh.

A further goal of the present invention is to provide visualization fora user based on any combination of selectable parameters, includingcombination of the parameters, and to display the applicable portion ofthe geography in a modified way, exposing or highlighting areas of bestfit or fitting certain combinations of parameters. Such visualizationmay include but not be limited to color, size, shading displays, foggingor labels in context with the subject sub-market, property orneighborhood. In one such example, because the data are regularlyupdated, a geographic augmented reality view can show present locationsof scaffolding and can be used to identify to a user a walking pathbased on current or anticipated weather. In another example, theaugmented reality visualization can represent a change in availablespace (e.g., an apartment or retail space) for rent or available spacethat meets a certain search criteria such as area size, rental rate,building class, building operating costs, etc.

The system of the present invention includes a relational database and aGUI, in combination with an at least x86 consumer central processingunits (CPU) and consumer graphics processing units (GPUs) for handlingGUI display on an external monitor, command input from a touch screen orexternal mouse and keyboard, database queries and display on an externaldisplay.

The technology of the present invention identifies, stores, andvisualizes real estate information by curating and storing thecoordinates of parcels, buildings, floors, units, building elements andinfrastructure (cooling towers, water tanks, cellular towers, etc.) witha process that involves manipulating property footprints to matchbuildings at various elevations and creating a coordinate bed (FIG. 1 )of possible coordinate options for a user to trap in order to identifyand organize regions of the reality mesh.

Conventional smart city GIS systems use shapefiles or unique 3D modelsof buildings with graduating levels of detail (LOD) aggregated into avirtual city model. The advantage of the solution in this invention isthat it allows for a reality mesh to be used for communicating uniquebuilding and floor data, which is otherwise impossible without theunderlying coordinate association knowledge on a per-property basis.

The visualizations of the present invention are comprehensibly clickableso as to allow a user to zoom in, zoom out, or obtain additional overlaydata. In other words any spatial area of the real estate market,sub-market, building, floor, window, or architectural element, asexamples, can be clicked by the user or highlighted by the system todisplay more information.

The present invention uses a plurality of data sources, such as but notlimited to government records of properties and real estate listings ofproperties, among others, is potentially including both public andprivate sources. One such data source is actual images taken fromoverhead airborne or satellite devices which provide a structuralstarting point for the visualization. These initial images, which couldbe of varying radii to be limited to a building or extend to a city, arepreferably high resolution images, usable by the present invention tocreate the beginnings of an augmented reality approach to visualizingthe selected area. In the methods of the present invention, the imagesare processed, at least in part, to more precisely identify edges andother attributes of buildings. These edges are then used in combinationwith other data obtained from additional sources, to form an augmentedreality visual display building by building which can be furtheraugmented based on factors such as but not limited to user or systemselection. In addition, the scale of the visualization may be adjustablebased on user or system selection.

The listings in these data sources may include images of buildings andunits, together with dimensional information among other data. All thedata from the sources, which may include public and private sources,obtained by the system of the present invention are preferably regularlyupdated and comparison is regularly made to prior received data (or anormalized version) to recognize which updates are appropriately new andwhich, for example, might be temporary or an error. Various types oferror control checking exist in the system. In one example, floor-levelerror checking may be used and includes determining the correct spatiallocation of a floor in a building or a unit on a floor. This can be donefor several units on a floor, but becomes more complicated when workingwith spatial representations of units with a 3D building model.Floor-level checking is conducted by:

-   -   A) Examining units by using available data regarding similar        type units on neighboring floors or similar buildings. In modern        buildings, residential floors typically have the same column        spacing and unit distribution between floors and if new data is        received that is inconsistent with the known column spacing or        divided floor layout, the system of the present invention can        identify these anomalies when they are highlighted in the        reality mesh, such as but not limited to visual comparisons.    -   B) Floor-level checking is also performed automatically by        preventing the adding of unit coordinates that overlap the same        region of the floor. This is done by identifying matching        surface areas from a newly added or updated unit and preventing        the system from parsing the matching coordinates into the        database.

Preferably received images should be of high resolution but need not be.These images may show structural variations, such as elevated or loweredceilings, potentially together with appliances and fixtures. The systemof the present invention takes into account these images together withany available related data which may be stored or later stored in anormalized form in the data base of the present invention, such asdimensional information, and creates a multidimensional model andvisualization of the building, floor, unit, land parcel or buildingarchitectural element or feature such as rooftop infrastructure such asbut not limited to a cooling tower, water tower, HVAC equipment,cellular transmitter, electrical generator or solar panel.

A graphical user interface associated with or a part of the system ofthe present invention allows a user to interact with the visualizationin any number of ways, such as but not limited to rotating the image orreplacing elements in the images.

The data sources used by the present invention are extensive and includegovernmental and non-governmental sources. The system of the presentinvention includes a processor (which may actually be a plurality ofprocessors distributed such as in a mesh network) which is programmed topoll data sources on a frequent basis, such as a regular basis, toupdate data previously obtained. A listing of exemplary data sources isincluded as Appendix 1. Consequently, the system of the presentinvention includes one or more databases, typically relational innature, where the databases may be reconfigurable on demand,automatically or otherwise. The processor of the present inventioninteracts with the databases and also with a specialized graphical userinterface, where a user can select any of several parameters to show ona developed image for a desired building, unit, or area. That image maybe maneuverable by the system and/or a user, such as being rotatableand/or changing perspective by the user so that attributes of threedimensions can be displayed and/or distinguished, often in highresolution. Such imaging can include specific fixtures and the like.

In summary, the system of the present invention regularly polls datasources to create and update one or more database fields with the foundentries and uses these entries in visualizations created and/orrecreated by the processor of the present invention.

Selection of attributes to display may be user controlled and/or systemcontrolled and selectable. Users can select using the GUI, either byclicking on a map, an object, selecting from a menu, voice activation,or a combination.

Further, the data sources can be used to overlay the images with one ormore additional dimensions, such as but not limited to operating cost ortax data and calculated data, such as rents, common ownership, foreignownership or market value. Other real estate examples include propertytransaction details such as the seller name, buyer name, sale price, andpercent interest of property transferred, to name a few. Buildingmechanical examples include elevator inspection dates, boiler make andinspection dates, cooling tower make, capacity, and serial number, toname a few. Health and environmental examples may include the presenceand/or duration and/or timeframes of debris, rodents, birds, inside airparticulate levels, or biological growth in a building's water tank orair handling equipment, and the like. These overlays can take numerousforms, such as but not limited to expanding/contracting portions of ageographic area or real estate market or submarket, a building orbuildings, a building floor or unit on one or a multitude of buildings,changing colors such as to highlight selected market, submarket,building or buildings, or selecting buildings or units for directcomparison. Again, all of these displays preferably are created fordisplay in an augmented reality sense so that a user can seemulti-layered reality visualization of particular buildings, units, orareas together with desired and/or related data, where the visualizationencompasses the data in some way. The actual visualizations may be useradjustable and may be created/displayed at least in part using augmentedreality, such as to customize based on a particular user's expressed orinferred desires.

Some of these data sources may be private sources. For some users, theprivate source data may be combined with public source data, which maypermit for user-specific visualizations. In other cases, the privatesource data may be filtered through an anonymization routine so as toobscure data which could be used to identify the source or to keepprivate data specific to a particular lease, property appraisal reportor mechanical contract, as examples.

Many cities provide the coordinate boundaries of properties as part ofopen data initiatives. These coordinates typically originate fromlegacy/historical GIS systems and provide an association between aparcel and a city's unique identifier code (ID) used for taxing orplanning purposes. However, we have observed that such data can beerror-laden, and have developed algorithmic-based approaches to“cleaning” the data (e.g., determining which data are errors) beforeupdating or reconfiguring the system's database.

Additionally, because data available from multiple sources are notnecessarily structurally consistent with one another, the system of thepresent invention includes routines for a process to calibrate (ornormalize) the data such that it can be stored in a uniform structuredway. As one can imagine, calls to the data might be frequent and thescope of such data may require extensive processing so uniformity instorage is vital to the user experience.

Further, because at least some data, such as geographic data, are storedin public systems with appreciable history, the data are not alwaysaccurate as they relate to a precise reality mesh depiction of the realworld and the calibration process needs to compensate for this lack ofaccuracy. For example, building coordinates may be slightly off,spatially, in data sources, and it is important to correct for this. Itis corrected in the present invention preferably at least in part basedon the previously discussed overhead (e.g., aircraft) images used tomake manual coordinate adjustments. Further, because data are constantlyupdated by cities and municipalities, among other sources, these errorscan reenter the system of the present invention, so the presentinvention includes routines to “check” for re-introduction of error andavoid them happening as a part of the calibration process. This is asignificant point, because some changes might be accurate—such as newconstruction, and the present invention includes processing capabilityto discern re-introduction of errors and temporary changes (e.g.,scaffolding) from proper changes.

The system of the present invention's (“system”) process uses visualreporting, for example in a virtual globe within a web app (orcomparable element or engine), to visualize the status of the system'scoordinate fixing process. Visual reporting allows us to load anycoordinate set and quickly toggle between original or alteredcoordinates on or off, revealing differences visually using, as anexample, primary colors. For example, if the system's original(government sourced) coordinates are stylized red and alteredcoordinates are stylized yellow, areas of finished work within thereality mesh may appear in orange and areas requiring coordinateadjustment work may be red. This visual reporting also allows users toadjust the brightness, contrast, hue, saturation and gamma imagery tobetter expose building coordinates that require calibration. By cyclingthrough different combinations, the regions of the mesh with variousreal world imagery texture colors can be better surveyed to visuallyidentify alignment problems requiring work to fix.

Original coordinates vs. altered coordinates. FIGS. 2 and 3 show theoriginal footprint coordinates in yellow, overlaid with the system'saltered coordinates in red in a manual portion of the process (althoughthis may be automated on a parcel-level as well). This allows thesystem's algorithm to identify buildings with base coordinate sets isthat need to be adjusted to fit the reality mesh.

It is apparent from the distortions along the surfaces of the meshgeometry that the original coordinates (yellow) do not fit the buildingsin the reality mesh and need to be adjusted. The adjusted coordinatesare acceptable and can be used by the application. This reporting toolalso allows both coordinates to be displayed at once to permit manual orautomatic checking.

Once calibrated, the coordinates are then “core” to the system and canbe used to correctly highlight buildings and legal property boundarieswithin the reality mesh. Without such calibration there can beunnecessary and confusing distortion and incorrect highlightpositioning, especially in dense urban areas such as Lower Manhattan.

Regarding overlay with financial data or other data affords “what if”scenarios which can be achieved by user selectable filtering.

Because of the volume of data and the need to call data in differentways for visualization, file compression technology may be used tocompress the data and streamline delivery of results. Briefly, varioustechniques are usable but they need to be consistent with both the datastorage and delivery processes. At present, the system uses a privatecloud-based file server that can actively compress reality mesh filesbefore sending them to the client's graphical user interface, butalternative comparable techniques can be used such as virtual hostingservices from Amazon AWS or Microsoft Azure. Also, content distributionsystems (CDN) are used to improve hosting and file server performance.

Once the database is setup and data are regularly updated, the use ofthe database in combination with the user interface is extensive.Appendix 2 provides a listing of many example use cases for the core ofthe present invention. It is believed that every one of these is bothnovel and differentiable in numerous ways from prior approaches.

Benefits of the present invention:

-   -   Increased speed of communication of property and market        information to stakeholders.    -   Improved accurate comparison between real world data and        government or private property databases, usable for numerous        analyses and improved results and decision making.    -   New insights from combining multiple datasets in a 3D spatial        context, taking advantage of reality mesh transparency, fogging,        timespan capabilities and simulation capabilities such as        weather, smoke, fire, flooding and precise contextual        information callouts.    -   Instant reflection of new data in a real world representation.    -   Democratization of data with reduced information arbitrage on        assets.    -   Maximizing property value by comparing performance on peer        properties.    -   Improved pricing based on the most current data to aid in        accelerating sales cycles.    -   Bring transparency to the real estate market by seeing all        available space options in a market, not just those spaces        presented to a consumer by a broker.    -   Real time searches for apartments available for rent or sale. Or        office space for sale or lease.    -   All sales transactions for any type of property can be searched        and the details for each sale can be examined.    -   The graphical user interface can present all or a selection of        the application's data visualizations as automated slide shows        that play with constantly updated data, customized to the        industry role of the user, substantially reducing the amount of        time necessary to communicate changes in the real estate market.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 depicts property footprints to match buildings at variouselevations and create a coordinate bed.

FIG. 2 depicts unadjusted property footprint coordinates projected ontoreality mesh in the present invention.

FIG. 3 depicts adjusted property footprint coordinates projected ontoreality mesh in the present invention.

FIG. 4 provides an architectural perspective of the various componentsof the present invention.

FIG. 5 shows an example of how, in the present invention, one canvisualize how market participants can research ownership and history ofa unit or building or market prior to renting or purchasing. The infoboxin the GUI shows the selected units floorplan.

FIG. 6 shows an example of how, in the present invention, one canvisualize how market participants can research ownership and history ofa unit or building or market prior to renting or purchasing. The infoboxin the GUI shows financial information for the selected unit.

FIG. 7 shows an example of a visualization of shows available officespace in the present invention.

FIG. 8 shows an example of a visualization of NYC property tax by squarefoot in the present invention.

FIG. 9 shows an example of a visualization of NYC property tax by squarefoot for peer properties in the present invention.

FIG. 10 shows an example of a visualization of complaints as used in thepresent invention.

FIG. 11 shows an example of a visualization of complaints as used in thepresent invention.

FIG. 12 provides a diagram. the data hierarchy within the system andindicates the nature of the data contained

FIG. 13 provides a sample infrastructure diagram of the presentinvention.

FIG. 14 shows an example of the operational process to inspect, modifyor create matching mesh coordinates to match a building envelope.

FIG. 15 shows an example of the fog effect where buildings containingquery results are shown without the fog effect so that they are usablein the present invention.

FIG. 16 shows an example of the integration of the core coordinates madeby the coordinate bed selection.

FIG. 17 shows an example of the system whereby coordinate data is usedto highlight buildings based on a color coded range of city zoningcategories in the present invention.

FIG. 18 illustrates how existing and potential Floor to Area Ratio (FAR)differences can be represented in the present invention.

FIG. 19 details speech commands precisely being accepted by the presentinvention, processed by a speech-to-text processor and converted to atext command in the present invention.

FIG. 20 provides an example of Mark to Market Analysis in the presentinvention.

FIG. 21 shows further attributes available for analysis in the presentinvention.

FIG. 22 displays updated altitude of the polygon control surface of thepresent invention.

FIG. 23 shows an example workflow of data during a typical user session.

FIG. 24 depicts the PropSee Application Infrastructure Customization ofthe present invention.

FIG. 25 depicts PropSee Application Infrastructure for Web.

FIG. 26 depicts PropSee Application Infrastructure iPad Standalone.

FIG. 27 illustrates a submarket selected in lower Manhattan by applyinga fog effect to unselected area.

FIG. 28 depicts a solution for fog solution grouping for residentialbuildings.

FIG. 29 shows an example of inverse mesh clipping logic.

FIG. 30 depicts the GUI used to manually position the floorplan in themesh.

FIG. 31 explains the logic used by the system to choose the viewingdirection from partial suite coordinates.

FIG. 32 is an example of visualized elevator cores inside a building inthe reality mesh using the system's building coordinate data.

FIG. 33 depicts the systems use of floating lines in the GUI.

FIG. 34 shows rooftop infrastructure highlighted in the reality meshthat is part of the system.

FIG. 35 is an example of building centroid lines connected to indicateshared infrastructure ownership.

DETAILED DESCRIPTION OF THE PRESENT INVENTION

The invention can be thought of as having two core parts: the first partis a system and method to collect, organize, relate, and embedgeographic real estate information, related information, and physicalbuilding representations, relate them to one another and use some or allof the information to form a photogrammetric reality mesh. The secondpart comprises a system and method to search, analyze (or to educatedwith), and display (or present) processed information for purposesincluding but not limited to market data and statistics and financialanalysis and potentially include conclusions based on “what if”scenarios.

The present invention requires consumer grade x86 CPU and 3D graphicsaccelerated GPU capabilities to operate. Further, the invention requiresa sufficiently high resolution display (1080p) to properly fit the GISand reality mesh inside the GUI while presenting infoboxes with legiblysized text to the user. The invention requires access to a large datastorage device containing a relational database that is connectedlocally or via the internet of at least one gigabyte in size but willoperate with more data and more information if the data store is onehundred gigabytes for a municipality on the scale of New York City.

The present invention is further directed to a processor-based use of arelational database in combination with a GUI for allowing a user toselect attributes for display or further study or display, such that theGUI and its display are self-adjusting based on the selected parameters.The GUI selection may be based on clicks, voice input prompts, and/ormenu selections, as examples. The display itself may be selectable, suchas but not limited to clickable, as well.

The present invention is further directed to one or more physicaldisplays with visualizations (referred to herein as visualizations ordisplays), modified based on system and/or user selection, where thedisplays embed pertinent information within a presentation, preferablyan augmented reality-based presentation, where the displays may includegradients consequential to retrieved relevant data. Color gradients arethoughtfully considered and defined to reveal data outliers and requireknowledge of the operational domain (e.g., boiler capacity) or businessrules (e.g., tax assessment and abatement), market rents, and expenses,etc. of a dataset being visualized. In other words, the presentinvention is directed at least in part to providing visualizations ofreal estate data, overlaid on portions of real estate and/or buildings,such that the appearance conveys information based on at least content,color, fogging and shading and/or highlighting.

The present invention is further directed to a database update and/orreconfiguration methodology based on regular retrieval of data from awealth of sources, said retrieved data resulting in on-goingmodification of selectable menu items in the user GUI.

The present invention is further directed to implementation of machinelearning techniques usable to do any or all of the database repopulationand/or reconfiguration and GUI reconfiguration, where the GUIreconfiguration can be based on any combination of user roles, selectionand attributable fields or entries in the database.

The present invention is also directed to methodology for volumetricmesh highlighting, where the highlighted area may be highlighted in anynumber of ways including but not limited to, color oropacity/transparency, and highlighting is preferably, based onselectability by either or both of the processor of the presentinvention and user roles. Examples of user roles include, but are notlimited to, real estate brokers, tenants, property owners, lenders,portfolio analysts, property appraisers, architects, equity analysts,mechanical contractors, property developers, investment advisors,bankers, REIT analysts, elevator, air handling and fire-suppressionsystem contractors, filmmakers and video game developers.

In at least some situations, as described herein potentially amongothers, forms are used in the present invention for data structuresand/or input.

The present invention includes a system as shown in the architecture ofFIG. 4 . The system of the present invention preferably includes anonline, internet-based file storage system, relational databaseback-end, front-end client application containing a GUI and a front-endclient application containing a dashboard to control user access andsystem data. While shown and discussed herein that the system includes adatabase, a processor, and applications, each of these may be deployedas a plurality of such elements or devices, and these elements ordevices may be distributed across locations and/or arranged in an arrayconfiguration. Nothing should be construed herein that an element or adevice described in the singular is necessarily a single element ordevice.

The system has the capability to be deployed in an “offline” mannerwithout the need for an internet connection. This paradigm of systemdeployment is described in FIG. 13 where the specific need is to runwithout access to the internet and so the system contains all necessarybasemaps (vector ground maps), reality mesh models, single buildingmodels, real estate market datasets, building datasets, city, state andfederal government datasets, property transaction datasets, userinformation, user security information, GUI framework and web browser ona stored local disk on a mobile or desktop computing device connected toan external display with sufficiently high resolution (1080p or higher)to operate the GIS and reality mesh with fidelity and interact with thedata selectability with the mesh or data selectability with theinfoboxes. This same device can also be connected to a head mounteddisplay or optical augmented reality glasses device to project the GISand reality mesh and infoboxes is directly in front or overtop of theuser's view plane or range of vision in a manner that is spatiallymatched to the geographic context in proximity to the user'scurrent/present or other located area. This implementation of theinvention allows the user to stand in front of a building and look up atit and see data attributes about the building, such as propertyinformation, available office or residential space for sale or lease,historical property details, city permits, complaints, tax information,utility consumption data or any other data variable relevant to thesubject property or nearby properties to the user querying the system.Comparably, this implementation of the invention also allows the user tonot be present and remotely examine the data attributes of a buildingusing stored imagery of the real estate submarket, building or floorbeing examined.

Volumetric mesh highlighting techniques are discussed herein forbuildings, floors, and architectural elements, mechanical, oroperational elements of a building, which can be visualized within themesh imagery textures and geometry or any coordinates inside, on thesurface or outside of the mesh. The polygon mesh model can be enhancedto articulate elements, including but not limited to, real estate marketor submarket performance, changes in real estate market or submarketperformance over time, building ceiling heights, amenity space, healthsafety, health check in stations, window locations, door locations,rooftop water tanks, rooftop HVAC infrastructure, cooling towers,signage, life safety, outdoor terraces, rooftop solar potential, andfaçade inspection dates.

In order to operate, the system takes into consideration the position ofthe reality mesh in 3D space, preferably on a cartesian plane. The meshis aligned within a virtual globe (aligned with a mathematicalrepresentation of geopositioning on a real Earth-shaped globe)preferably using a cartesian coordinate system and digital elevationmodel. The typical presentation of the mesh is drawn, or projected, ontop of a two dimensional satellite image map of the exact location, butthe system is not limited to this and can present other base maps, suchas nighttime satellite imagery, flood maps, or base maps with specialstylistic and/or information design functions. Base maps and othervector-based mapping data can also be raised above the reality mesh todepict road names, flooding and evacuation zones, and so on.

Application of the system operating with a reality mesh also exists forvideo gaming and film production. The system can generate user interfaceelements for buildings, neighborhoods and cities that can be consumed byvideo game and cinematic editing software for use in those domains. Forexample the system can present areas of the reality mesh in a fog thatcan be contextually consistent with the plot or premise of a video gameor cinematic production.

The position of the reality mesh and the system's stored coordinate datafrom the coordinate trapping process are relative to each other. Asupdated reality mesh files are added to the system they must bepositioned with the same alignment coordinates used with the originalmesh used for coordinate trapping. The mesh contains only exteriorimagery of a structure. No internal imagery exists within the realitymesh relative to the building structure, internally it is a void. Anassumption generally used and made herein is that the position of thereality mesh is always true and accurate to real-world position ofreal-world cities and building.

The user makes selections within the GUI by using several methods.Chiefly, the GUI presents the user with the ability to select any regionof the reality mesh, be it a real estate market, submarket, building,floor, suite or window. The selectability can be indicated by an icon,fogging, style change by means of color, style change by means oflighting projected by the GUI on the reality mesh, style change by meansof opacity/transparency of the mesh, style change by means of clippingor removing sections of the mesh to illustrate only one or multipleparcels or properties, style change by means of applying an opaque fogto the mesh and “punching holes” in the mesh to indicate buildingsexclusive of those included within the opaque fog. The user can alsomake selections by means of information boxes (infoboxes) drawn withinthe GUI that contain lists and tables of information generated fromuser-queries or standard reporting of information stored in thedatabase. The user can select the names, addresses or unique identifiersof buildings in the infoboxes to open more detailed information thatdepict metadata or other information related to the infobox report. Theinfoboxes can also contain imagery that is unit specific, such aspictures of a bedroom or kitchen for residential units or pictures of anoffice space layout for office units The infoboxes can also containcharts to show data presented in various user selectable chart formatssuch as historical bar graphs providing information on rental rates ortax changes. The infoboxes can be positioned relative to a buildingwithin context to the reality mesh or not, using lines that connect thereality mesh to the infobox, depending on the need for the GUI to relateinfoboxes to specific buildings or a real estate submarket orneighborhood to be relevant to the user.

The system's reality mesh is delivered to a user's GUI as a compressedstream of texture imagery files, typically in PNG format, combined withvector geometry data, organized as a tileset for efficient drawingperformance by the CPU and GPU. Various compression protocols can beemployed that provide differing levels of data size reduction dependingon the client system platform. For example, compression protocols forreality mesh files used for Android devices and other devices mayrequire different compression protocols, from those necessary for AppleiOS devices. These compression techniques are important because highresolution reality mesh files are very large and demanding ontraditional consumer computing hardware and especially on mobiledevices. With high speed wireless technologies like 5G, the issue issomewhat mitigated. Client devices require commonly found consumervideogame 3D graphics processing capability to run the application withfidelity. The CPU and GPU processing power in a current 5G mobile phoneis sufficient to power the application. System memory requirements arenot high because the system can buffer the necessary imagery texturesinto and out of memory as the GUI scrolls through the reality mesh andloads and discards imagery textures accordingly based on the contents ofthe display.

Virtual globe software allows for a multitude of stylization effectsexclusive to GIS software. The list of common stylization effectsincludes, but is not limited to: drawing 2D or 3D geometry, highlightingtopography, delineating topographic features including topographicsetbacks, inserting other 3D models, inserting 2D images, applying othertexture images to building or other shapefiles, tinting the display,realigning loaded elements, colorizing, clipping (deleting, or removingportions of the reality mesh with a horizontal plane), drawing vectorlines relative to the mesh and screen elements, measurement, and labelor icon placement and positioning relative to the users view of thedisplay. These virtual globe stylizations can also be used during theprocess of capturing coordinate data that the system creates through themanual coordinate trapping process or through interaction with any otherGIS stylization effect. The employment of multiple effects can enhancethe system GUI and ameliorate the user's understanding of informationfrom the system's display. For example, colorizing every building withhigh rates of bedbugs in New York City, while highlighting all the unitsin the available apartment market, is an efficient method to filterpossible options.

Sample insights gained for comparing multiple datasets: the systemreveals important insights when two or more government or privateproperty datasets are combined in the same view. This allows marketparticipants to comprehensively research the ownership and history of aresidential or office unit or building or neighborhood or submarketprior to renting or purchasing, as well as identifying mortgages onproperties with high loan to value ratios that are more likely todefault. Also, identifying properties with above average square footpricing could predict greater challenge in profitability. See FIGS. 5and 6 .

As shown in Example A (in FIG. 5 and FIG. 6 ), the system can load it'sResiRental (residential rental units available for rent) visualizationof the available apartment inventory with the city ACRIS (Automated CityRegister Information System) data.

Example B (FIG. 7 ) shows an example of available office space indowntown and NYC Department of Health and Mental Health (DOHMH) IndoorEnvironmental is Complaints, which reveals space options that are inbuildings with reports of problematic indoor air quality, indoor sewageproblems, asbestos, or mold.

Functions within visualizations: When the system loads the datanecessary to create a visualization, it presents the capability to applyfunctions to the retrieved data stored in the database to alter theloaded stylization using other parameters. Example A as shown in FIGS. 8and 9 shows NYC property tax by square foot for buildings downtown. Whenthe user selects a building, the GUI presents a function in the infoboxcalled Tax Difference which changes the stylization to show an adjustedvisualization showing tax per square foot related to the selectedbuilding coloring, for example, red or blue highlighting, to indicatemore or less real estate taxes on the indicated buildings. This can alsobe performed for only peer properties, such as similarly classed officebuildings. In another example, this visualization function can beapplied to office tenants who commonly take on an obligation to paytheir pro-rata share of tax increases above the base year, which is theyear the lease was signed in. The user interface visualization can becolorized to show this change in percent increase in real estate taxesfor space in a single or multiple buildings over time. Using thiscapability, a tenant can use the system to assess if they will pay moreor less tax, which is of benefit to them and, for example, whether thetax structure has been applied in a fair manner.

Example B, including FIGS. 10 and 11 , shows New York City Department ofBuilding (DOB) Complaints over an area of the Tribeca sub-market, withthe building 56 Leonard Street highlighted in white in the GUI. Theinfobox reveals a list of DOB complaints by category. Each differentcategory is also a function and selecting any category will filter theresults set by buildings with matching complaint categories. In thisexample the system shows an example of illegal hotel rooms inresidential buildings which is a growing problem in cities with theemergence of online room rental services such as AirBnB and VacationRentals By Owner (VRBO).

The system further integrates building footprint data made availablefrom public sources with unique building identifiers to relate allinformation in the system. The system's geographic hierarchy is bycountry, state, county, city, market, submarket, neighborhood, building,floor, unit, and equipment/infrastructure item. By leveraging the publicand private ecosystems of unique property identifiers, the system canselect and visualize all geographic entities at a discrete level andtreat each entity uniquely within the system interface to visualize anyassociated datum. Examples of associated datum, or metadata, include butare not limited to ownership, transaction history, municipal zoning,property tax records, government regulated condominium plans, commercialand residential property rent and vacancy rates, properties underlitigation, energy, water and gas utility consumption meter data, healthand education department data, fire and life safety data, insuranceflood risk, building maintenance and operating data, property financialdata, investment market data, restaurant inspections, current andhistorical hotel booking activity from travel company affiliate datafeeds, crime activity, proximity to metro stations and the frequency ofa population testing positive for a pathogen such as Covid-19. Eachdatum can be tracked, such as over time, and the changes visualized inthe system using common unique property identifiers from government andprivate property datasets. Unique identifiers from these externaldatasets are joined with the system-defined unique identifiers by theorder they are either added or matched by a manual or automatic joiningprocess used by the system when a property is added. An example of anautomatic joining process is to join building IDs with matching buildingaddresses. An example of a manual joining process is of a user creatinga join (stored in a database table) to building identifiers withdifferent legal addresses but comprising the same physical structure.

Concepts such as but not limited to highlighting a region of realitymesh are core to this invention. Highlighting can be visible orinvisible and may use high opacity values for reality mesh regions toproduce transparency in the reality mesh. One reason to producetransparency in the reality mesh is to mimic the appearance of buildingwindows. An important part of this invention is how the system enablesthe selection of real-world objects within the mesh, either via a GUI orotherwise within the system of the present invention itself. Withoutthis process the system would be unable to classify or identify legalparcels within the reality mesh beyond indicating single points withlatitude and longitude values. Importantly, government-sourced parcelcoordinates are typically stored in legacy system formats calledcadastral maps, which are recordings of property boundaries collectedfrom many decades of government land management processes using a manualline-of-sight surveying technique that is not exact to the real worldurban fabric. Different levels and generations of government also havevarying standards of accuracy within their legacy land managementsystems that make their publicly provided property data more or lessaccurate. Further, urban areas with histories of buildings being demised(divided into different legal or functional properties) are often notreflected in public data with consistent standards. Additionally, thereare few private market sources of property data stored at building orfloor-level formats with common standards for cities and counties in theUnited States, Canada and countries in Europe. Therefore, the system ofthe present invention compensates for those unknowns by using thegovernment supplied coordinate data only as a starting point and sourceof unique identifiers, generating the necessary property coordinatesusing the precision created by the system's human operators using thereality mesh coordinate trapping technique.

The present invention uses its reality mesh selected data sources toamass data, arrange the data in the database of the present invention,and use the processed result to at least formulate visualizations at anyor all of these levels, at least in response to demand to do so. Westerngovernments tend to organize property data by structures and taxablelots, so the system of the present invention uses an organizationalmethod based on a similar paradigm that allows for fast and intuitivedata queries. If a jurisdiction uses an alternate approach, the systemcan adjust accordingly with “normalized” data. Using a transparenthighlight technique allows the system to create a user interface thatsupports touching or clicking a building and interacting with it byfloor, unit, window or superstructure.

New York City is an excellent choice in the United States for an examplehere because of an assortment of Local Laws (see LL84) that have beenpassed that require disclosure of a great number of city data metricsand because New York City has an extensive data tracking program fortracking numerous aspects of properties. This is important because itallows for business models that depend on city disclosed data toprovide/facilitate products and services. In general, these data sourcesare public but different ones may need to be normalized by the system ofthe present invention to be most useful. In the methods of the presentinvention, the data from these data sources are pulled directly orindirectly into the database and may be supplemented by other data, suchas private data, from these or other sources.

FIG. 12 diagrams the data hierarchy within the system of the presentinvention and indicates the nature of the data contained. New York Cityis used as an example in this description but could be substituted withany city, county or other government body that provides public access totax lot information and/or corresponding unique tax lot identifiers andany relatable or applicable city, county or other government bodydatasets. Applicable government datasets that are not related to uniqueproperties but only regions, such as climate change and flooding data,are also used by the system to stylize the reality mesh and presentinformation to users.

In the example detailed in FIG. 12 , an open-source virtual globeapplication, such as NASA's WorldWind, CesiumJS, or an open source WebGLviewer such as three.js, can be used to create or simulate a traditionalGIS application environment that projects a reality mesh on a cartesianplane in a 3D environment with real world scale and physics. This is animportant distinction because the system and methods detailed herein arenot limited to any GIS application or web browser and all describedfunctionality herein can be replicated in a 3D environment withsufficient capability to load a reality mesh and perform stylizationeffects upon said reality mesh. The reality mesh can be drawn at variousresolutions and higher resolutions demand more in computing resources.Check infrastructure diagram, FIG. 13 , below.

Once the reality mesh is loaded and applied, it can be interacted withusing the coordinate data stored in the system's database. This data isconstructed as 2D or 3D is polygons of various dimensions and sizes,otherwise described as volumetric regions of the reality mesh. Theseregions act as GUI contact points for building surfaces and allow theuser to accurately and intuitively select any portion of a building thatcan be inferred from the reality mesh resolution. Because the examplemesh uses extremely high-resolution image texture mesh of 2 cm=1 pixel,the detail is very high, and features as small as spray paint onman-hole covers can be discerned, as well as the makes and models ofrooftop HVAC equipment and cellular antennas. This is very important tothe system because it allows the user to accurately assess all aspectsof a building due to the crispness of the image quality in the GUI.

All components of the application are preferably deployed in aclient-server relationship across the public internet or in an offline,standalone design where the system and applications can run on a mobileor desktop computer running a local web browser, local web server, localcopy of the web application and local copy of the database. A secureHTTPS connection may be required to operate the online implementation ofthe system over the public internet.

The system provides a user interface deployable on a client device inboth online and offline modes through a web browser, web server, webapplication and database and can be controlled with a mouse, touchscreenenabled device, or voice input. See FIG. 13 . The GUI can also beexported by the user as a graphic or rendered into a video format sothat the information can be used offline.

The operational process to inspect, modify or create matching meshcoordinates to match a building envelope in the reality mesh is detailedin FIG. 14 . The method includes an important process for creating andadjusting a two-dimensional coordinate-defined polygon, such as abuilding footprint. First, the government supplied (legacy) coordinatesare associated with a unique building identifier (system, building ID)and any unique identifiers they contain (government IDs) are joined withthe new ID in the relational database. The legacy coordinate string isthen compared to a building representation in the reality mesh at grade(ground level) so that it can be altered to exclude the sidewalk and anyother infrastructure at grade that is not part of the normalizedstructure or legal (or otherwise) property. Altering to adjust thecoordinate string to match the building is performed by removingcoordinates that do not conform to the building envelope and adding newcoordinates that do match the building representation in the realitymesh. Coordinates matching the building envelope are saved in thesystem's database. Through this process triangulation errors can occurand they are distortions in the drawing system of a GIS that result fromcoordinates being drawn when stored in non-sequential strings. Forexample, to draw a polygon from coordinates a GIS must read all thecoordinates as sequential and distortions that appear as acute andobtuse triangles are created when the GIS draws coordinates that are outof linear sequence. Such errors may be created during this process ifaltered coordinates strings are inputted in a non-linear manner or ifcoordinates with non-sequential values are parsed into the database suchthat they overlap along edges, or as non-sequential strings. Ade-triangulation procedure is performed to individual buildings or toall buildings in a submarket to eliminate incorrectly placedcoordinates. Once cleared of triangulation errors, the coordinate stringis stored relative to a building ID and is ready to be used to highlightthe building.

An elevation bed of coordinates also needs to be created. This isrequired because the system needs a set of coordinates near to thesubject floor or building to be used to make precise selections forfixing buildings or creating partial coordinates for individual units.Many buildings require adjustments to their base coordinates and thisprocess produces the necessary adjustments to fit the reality mesh, todefine the unit boundaries on a divided (demised) floor, or to identifycoordinates for building infrastructure such as solar panels, rooftopbalconies, water towers, cooling towers, and/or other HVAC or mechanicalinfrastructure. The method of the present invention includes thisadjustment process.

The system's process presents an existing set of real-world coordinatesin spatial context with a subject property within the reality mesh. Thesystem does this by presenting it's known coordinates with asemi-transparent polygon surrounding the entire floor of a building.This provides a limited set of real-world coordinates that gives thesystem precise accuracy when a user selects a dividing point along thebuilding floor because no translations between various global andtraditional coordinate set systems needs to be made. To our knowledge,this present invention is the first application of such a process toform such precision and it forms the first known visualization withaccuracy for an augmented reality display. Essentially, the coordinateselection process has been simplified with a localized subset andpossible options supplied by a known selection of normalized coordinatesin the coordinate bed. This allows for precise alignment of units on afloor in context with the real-world imagery of the reality mesh. Thisis detailed in FIG. 1 using an example of the 8^(th) floor in 270Broadway, New York City. The coordinate bed encompasses the entirefloor, and the unit derived from a selection of the coordinates withinthe elevated coordinate bed results in a unit defined on the north eastcorner of the building.

The method of the present invention provides for a clean vector changeat the points of architectural articulation in a building structure.This is done by joining the first and last coordinate pairs from theknown selection set. The resulting effect is a clean highlight of thereality mesh at the corners of a building floor.

Each spatially defined floor or unit (e.g., a living or commercial unit)or portion of a floor representing common areas (e.g., elevator lobbies,hallways, or bathrooms) can be stored as a relational object in thedatabase of the present invention joined with the building table andvarious other related entities in the database. Obvious examples of suchunits are rental apartments, residential condominiums, leased officespace, office condominiums, lobbies, hotel rooms, mechanical rooms,janitorial storage rooms, utility access rooms, and computer serverfacilities.

The utility for stored coordinates of a unit or suite in a building aretimely with the advent of augmented reality applications and becomeuseful for virtual tours and virtual representations of space formarketing purposes. Further, the present invention includes methods formore advanced visualizations, including three-dimensional floorstacking. Stacking plans of a building are very important because oftheir ability to apply a colorization range to a building floor or unitand apply highlighting depicting information such as lease terminationdates, rental rates, transaction history, tenancies, available spaces,etc.

The application of this tool for examining the sales history ofapartment rental markets or condominium sales or building sales isapparent and novel.

The present invention further includes mesh clipping, which can be usedto clip (or remove from the GUI) portions of a building in the realitymesh at a selected altitude to allow a floorplan image or computer aideddesign (CAD) file to be situated in place within the reality mesh sothat the floorplan is positioned in the correct location and elevationwith accurate spatial orientation. The system's process to create theclipping coordinates necessary to support this capability is as follows:

-   -   1. A user or the system of the present invention finds a unique        ID for a building to create clipping and loads it using a        clipping editing form in the system's administrative tools. The        form positions the camera of the virtual globe to the correct        building ID in reality mesh.    -   2. The system checks to see if any existing clipping coordinates        exist in the system for selected building and loads these        coordinates. If not, the system uses default coordinates based        on the building centroid (center point at grade) coordinate and        core building coordinates.    -   3. The selected building is highlighted in the color red with a        partial transparency, and 4 horizontal clipping planes are drawn        perpendicularly to each other at 90-degree angles around the        building centroid, colored yellow, red, green and blue, all with        no transparency values.    -   4. Clicking on each plane, the user can increment or decrement        the proximity of the plane to the building façade, property        boundary or structural wall as evident in the reality mesh so        that the clipping fits the building.    -   5. Using two step adjustment controls on the clipping editing        form for larger or smaller steps, the user has the option of        incrementing or decrementing the proximity of the planes to the        building facade. Each of the step controls has a positive or        negative modifier to move the plane closer or further away from        the building.    -   6. After setting the desired parameters for the horizontal        planes, the system presents a slider on the GUI that allows the        user to automatically scroll through each floor of the building,        top to bottom, to see if the clipped planes show only the        desired elements of the building. At the same time, the system        displays any stored floorplans for selected buildings at the        same elevation as the displayed (clipped) floor in the reality        mesh so that user can check and edit (scale or rotate) the        floorplan orientation on a two-dimensional axis.    -   7. A user of the system of the present invention saves the new        or updated clipping plane coordinates in the system.

The system of the present invention provides an interface that allows animage of a conventional residential or office floorplan to be displayedat the correct elevation and position of the floor, with all portions ofthe reality mesh above the floorplan cleared from the GUI, or clipped.This allows for a much improved understanding of the subject space incontext with the building, local neighborhood and spatial region makingclear the view orientation and location of the unit in the building.

The subject building may be displayed with accurate (real-world)colorization, however for reasons of information presentation, designand emphasis, all of the surrounding urban fabric may be displayed in a“fogged” manner, such as in an opaque white, that mutes backgroundbuildings but bolsters emphasis of a building or buildings is beingindicated by the GUI.

Buildings with floors of various sizes are managed by creatingassociations between every image and floor. This allows for buildingssuch as One World Trade Center (example in FIG. 16 ) to accommodate adifferent image file and coordinate layout for every floor. Because thefloors of the example building change physical parameters at variouselevation ranges this is a critical feature to adapt the system to amultitude of architectural styles and massings.

The system of the present invention allows building improvements such asfurniture, HVAC equipment, security systems, security cameras,elevators, boilers, fire suppression equipment, plumbing infrastructure,etc., to be positioned to represent real world accuracy. Metadata suchas manufacturer, serial numbers, asset IDs, utility consumption data,equipment models and specifications can be stored and relatable in thedatabase to the precise spatial position of the equipment within thesystem's reality mesh. By including this data, equipment inspections canoccur faster and asset transfers when needed can be accelerated. Theexample of security cameras is important because of the capability forlaw enforcement to use the system to quickly identify cameras and cameraimaging systems that utilize facial recognition technology, positionedin areas that help with investigating criminal acts or gaps in securitycamera coverage because of the system's ability to precisely locate andhighlight security camera equipment. Additionally, any such metadataassociated with data feeds from city, county, state, national or othergovernmental bodies, or even real estate image archives and the like,can be associated and visualized with mesh coordinate data. For example,a state level of government could regulate that a certain type of airconditioning model or filter be installed in a certain type of retailbuilding (shopping malls) and the system could then visualize theexisting or planned air conditioning equipment or air conditioningupgrade in-situ within the retail building in the reality mesh. Bymatching permits for upgrades and energy consumption a visualization ofenergy efficient buildings with modern systems is possible. This is atremendously valuable feature for state governments to monitorcompliance with new regulations.

The use of this present invention includes building operations,inventory management, floorplan analysis, emergency services management,property and lease analysis inclusive of various other real estate uses,views, interior design, and machine learning implementations whereby thesystem can be used to recognize and match photos of a building to assistwith law enforcement investigations. This is done in the presentinvention by comparing the geometry and textures of the mesh withimagery of buildings so that a computer can perform a match.Additionally, building information management (BIM) data, demographicdata and traffic count data can also be used as sources of data that canbe visualized by the system.

When a floor is selected, such as by a user, and a floorplan isdisplayed, it is possible for the user to interact and receiveinformation about the building, floor, or unit by clicking on otherfloors that are highlighted (red in FIG. 16 ) and when clicked upon theymay change color, such as to yellow. In the example, a dotted polygonline is visible on the newly select floor. As seen in FIG. 16 , both thefloor highlight, the dotted line, and the clipped floor coordinates areall enabled and limited by the integration of the core coordinates madeby the coordinate bed selection. This process serves to furtherassociate the floorplan image with the data created in the previousprocesses. The GUI for this process is described in FIG. 16 , which isan example of the 73^(rd) floor of One World Trade Center, showing thefloorplan in situ on the plane of the clipped floor. The example of afurniture or floorplan layout is also visible in the figure along withthe “fog” stylization of the mesh. Floorplan layouts are important tocommercial and residential tenants because the layouts allow them tobetter differentiate space that fits their specific requirements. Thesystem's reality mesh clipping capability can also be used to remove aportion of a building or an entire building structure from the realitymesh at grade (ground level) or down to the foundation levels, exposingthe structure of the building's foundation. This is obviously veryuseful for exposing basements, parking structures, undergroundinfrastructure and foundation shoring down to the lowest level ofterrain under a building represented within the reality mesh.

This portion of this document details the applications and uses of themethods of the present invention.

Single-click-on-mesh record retrieval technique. The present method usesa relational database to store the system inputs from one or moregovernment or private source Application Programming Interfaces (API)which are automated processes to pull data from web services. An exampleof a government API is the City of New York's Open Data system. Anexample of a private API is the hotel booking system operated by thecompany Expedia. The system can also use exports from government opendata services, importing them as Comma Separated Value (CSV) or XML, orJSON data objects, and storing them in prearranged tables organized bylevels (city, state, federal) and departments of governments. The samedata input processes exist with private data services that can exportdata with unique identifiers as CSV or XML, or JSON data objects, andstoring them in prearranged tables organized by company and/or industryrole. Examples of this data include but are not limited to privatedatasets owned by landlords or other corporations that are normally usedby real estate data aggregators or real estate information companies.Other examples include data from government sources such as the City ofNew York's Department of Buildings (DOB) complaints, Division of Housingand Community Renewal (DHCR) registration forms, DOB violations, DOBpermits, Department of the Environment (DEP) asbestos data, Departmentof Finance (DOF) property tax, DOB façade safety, DOF financial recordssuch as deeds and mortgages stored in ACRIS, DOHMH restaurantinspections, Department of Sanitation (DSNY) graffiti tracking, DOBvacate orders, residential condo plans registered with the New YorkState Attorney's Office, DOB certificates of occupancy, New York HousingPreservation & Development (HPD) pest complaints (bed bugs, fleas,flies, mice, cockroaches, termites, and the like).

FIG. 17 details an example of the system whereby coordinate data is usedto highlight buildings based on a color coded range of city land usecategories. The selected building is indicated in red and linked to aninfobox displaying the results of the entity translation which retrievesa selection of building data from the relational database based on thebuilding selected in the reality mesh. The infobox has several tabs withdifferent data sources and, as an example, the ACRIS tab for New YorkCity is displayed. ACRIS is the Automated City Register InformationSystem managed by the Department of Finance in New York City to recordand manage property ownership, mortgage, tax, and other transactionalfinancial records. All property financial transaction documents areregistered in the system and made available to the public is with theunique identifier of the Borough Block Lot (BBL) code which is one ofNew York City's building identification methods, another being theBuilding Information Number (BIN) issued by the Department of Planning.Many cities and counties in the United States have similar ecosystems ofunique identifiers managed by municipal departments to manage propertydata. As a result of selecting a building from the system's realitymesh, the user may be presented immediately with all ACRIS documentsproduced by the query that originated with the building ID associatedwith the system inputs. One novel aspect about this method of retrievingACRIS documents is that the process to retrieve copies of tax documents,deeds, loan agreements, etc., is fast because only a region of the meshneeds to be selected once to produce every property transaction recordin the region. The benefit to this is the reduction in the time neededfor the system to execute the query in the database because of the verylarge number of municipal tax and property records stored in the City ofNew York's ACRIS system, as it is for all other municipal databasescontaining the legal and transaction documents necessary for localgovernments to catalogue tax lots and property records.

Any visualization returned by a query on the database to the GUI can berefined by user selected filters (key words) and parameters (dateranges) without a subsequent query to the system, improving performance.

In a first follow up example, if the user submits a query to return allof the City of New York's restaurant inspection data (see DOHMH)provided to the public with relational building IDs, the system couldhighlight every building that contains a restaurant for which it hasdata. The data could include metadata associated with every restaurantinspection such as the name of the restaurant, outdoor dining option,cuisine type, inspection date, inspection grade, violation description,etc. The system allows for any metadata field to be used as a filter toselect or eliminate matching results from the returned data set. Forexample, the system could select Mexican or Chinese cuisine types andthe visualization will update instantly with the new criteria. Thismethod of visual search analysis is very efficient because anindividual's abilities of perception can typically identify real-worldbuildings more quickly when seeing the actual building highlighted on amap as opposed to identifying a property from a list of addresses.

In a second follow up example, if a user submits a query to return allregistered mortgage agreements between all parties, the lender type(such as Bank of America, or Citi Bank) is available as a filter becauseit was included as metadata in the government data export added as afield in the database and can be used to highlight document results fordebtors, mortgagers, assignors, grantors, or lenders. Extending thisexample, a lender can quickly examine select issues across their loans,by geography.

In a third follow up example, if a user requests a result set thatincludes all available residential condominiums for sale or rent in acity or submarket, the result set will include all coordinates definingthe partial floor highlights in every unit. The result set will alsoinclude all of the metadata associated with residential condo marketssuch as asking price per square foot (PSF), unit size, last sale price,last sale date, or average per square foot pricing in a market,submarket, group of buildings, or specific building. Each of thesevalues can be used to create a spectrum of colorized result highlightsthroughout the mesh. More specifically, the proximity and line-of-sightviews of a selected unit's location of natural areas such as waterways,gardens, forests, parks, and coastlines apply upward pressure on marketvalue.

This method is expandable such that it also has utility when processinggovernment data that includes references to physically unique parts ofthe building, such as façade inspection scaffolding, water towers,cooling towers, cellular antennas, security cameras, etc., for at leasttwo reasons:

-   -   A) All building features can be precisely identified and        relationally stored in the database as objects using the present        methods.    -   B) User queries can take into consideration coordinate regions        when sorting infrastructure assets. Because the geospatial area        of a water tower, emergency generator or water cooler/chiller is        known, it can be represented in three-dimensional space,        highlighted with attributes or metadata, and communicated to a        user on various types of displays, specifically devices which        have the native ability to display augmented reality, like an        iPad, which can display the representation of building        infrastructure on its display using a camera capturing its real        world position. The coordinates that have been defined by manual        or automatic selection within the reality mesh in the present        method are required for this type of augmented reality        experience.

The user experience of the present invention is such that specificattributes can be selected for enhanced viewing. The GUI of the presentinvention may display an augmented reality version of the desiredattributes.

Another application for coordinate data is detailed in FIG. 18 whichillustrates how existing and potential Floor to Area Ratio (FAR)differences can be represented. FAR is a measure of the maximumbuildable area on a legal lot. There are often differences between theexisting floor area and what can be built according to municipal FARrules. FAR rules are applied to different building envelope size optionsbased on underlying zoning districts where FAR can be used in differentways. FAR calculations must also take into account the city zoning codeand be adjusted with the height limitation as of right for the relevantzoning for the selected property parcel or parcels. The system canreference the FAR and zoning allowances of a selected parcel'sneighboring lots to take into account “air right” trading potential ordensity maximization from nearby lots or properties. The presentinvention can visually project the potential buildable floor area overtop of the three-dimensional representation of the building in thereality mesh based in part on the customized building coordinates, whichare needed to upwardly project potential floor area in the preciseallowable location in context to the reality mesh. The system createsthis visualization considering the municipal zoning of the selectedproperty and it's immediately neighboring parcels.

The present invention allows for a stylized returned result technique,such as a city accented with white “fog” or “fogginess” over the streetsand buildings with some buildings or floors normalized with no fog.

FIG. 15 provided an example of the stylistic fog applied over a city toemphasize a single building, floor or unit containing no stylistic fogtreatment. This technique provides for an emphasis on the subjectbuilding(s) or floor(s) returned in the result set. This assists theapplication user or audience in understanding the spaces or propertiesreturned by a query.

Similarly, the results of GUI visualizations can be projected within thereality mesh so that only buildings with results returned by the queryappear with normalized real-world colors and all other regions of theurban area represented in three-dimensions by the reality mesh aredraped with a stylistic white fog.

This technique is only possible from the manipulation of the datacollected. Although it would be conceivably possible for anyone to applya colorization effect to a reality mesh, the ability to “punch holes init” at the same real world locations as buildings or floors requires asophisticated processing system, such as one of the present inventionthat contains all the coordinate data related to buildings within thereality mesh.

Speech Control. Sending the system commands using customized textstrings is particularly useful. On both mobile and desktop platforms,the system can accept speech commands to operate the application,interact with the reality mesh, and query stored real estate orgovernment data. Customized speech macros are stored by the system torecognize application functions to control the GUI and a camera on theuser device. These macros may include terms such as “spin” and “showoffice market” and “hide office market” and “show residential rentalmarket” and “show rents” and “hide rents” and “show availableapartments” and “hide available apartments” and “available condominiums”and “recent sales prices” and “recent sales prices on an average persquare foot basis in a certain submarket” and all relevant real estatedatabase fields and their variables and control modifiers (show, hide ornone) within the system. These customized speech commands can becombined into a macro command to build more complex queries.

FIG. 19 details speech commands precisely being accepted by theapplication, processed by a speech-to-text processor and converted to atext command. Of course, it is possible to program others. The commandcan be a simple action request on the application such as “spin the map”where the application orbits the camera around the reality mesh in theGUI, or a more complicated request whereby a command+database query isparsed by the speech converter. Example of such a query would be “showthe 20th floor of 61 Broadway” and the user interface flies through thevirtual globe to the stored camera position for 61 Broadway, the mesh isclipped at the 20th floor using the necessary stored data and exposingthe floor plan. Further, the user could say “Deed for 61 Broadway” andthe user interface would fly to the subject building in the reality meshand display the property deed in question, retrieving it from thesystem's association with the unique building ID.

The speech functionality also allows for the ad hoc highlighting of anybuilding or building floor with the spoken command “highlight 61Broadway” and the result is a call on the database to fetch thebuilding's base coordinates and encompassing the volumetric region ofthe buildings projection in the mesh with a colorized highlight.

Aggregated speech commands can be submitted in a string, for example“fly to 61 Broadway, One World Trade Centre and 28 Liberty” and theprocessed text command would result in the application GUI moving thevirtual globe's camera, giving the sensation of flight, to the mentionedbuildings, pausing at a specific angle for a short period beforecontinuing on to the next building. This can be further expanded byadding conditions such as “show the deeds for 61 Broadway and One WorldTrade Centre” where the GUI would fly to each building, display theproperty deed briefly at the predetermined camera position and continuethrough the sequence.

This can all be performed with the user speaking to the applicationafter enabling the application listener with a single click. In asimilar way, facial recognition can be is used.

Costs Comparison. The system includes a mechanism for comparing variouscosts such as but not limited to operating expenses and real estate taxexpenses in a subject building such as showing 1) expenses averagedacross a submarket, and/or 2) expenses averaged across similar classcommercial buildings (class A, B, C). These comparisons can also be madefor similar property types such as office, multifamily, residentialcondominiums, hotels, and leasehold positions on ground leases.

Examples of real estate operating expenses include but are not limitedto property insurance, repairs and maintenance, cleaning and janitorialservices, payroll, security, heating fuel, electricity, water and sewer,management fees, administrative fees. Real estate taxes are also storedin the database but organized independently of operating expenses. Eachof these is stored in the system and associated with each buildingrecord and its relational coordinate data.

The system can additionally produce a visual output of this analysissuch as in the GUI on any building represented in three-dimensionswithin the reality mesh.

Mark to Market Analysis. The system contains a mechanism for comparingthe existing rents in a building to what the market rents could achievetoday by calculating the differences and applying a capitalization rate(cap rate) to the difference, through this analysis the reasonable valueof a property can be estimated. FIG. 20 provides an example of thisanalysis. The system can produce a visual output of this analysis forany building represented in three-dimensions within the reality mesh.The mark to market analysis requires user assumptions of office rentalrates and varying cap rates to output a visualization of the valuedifference that can be achieved at a future point in time usingprojected market rents. The system can automate these calculations byascribing the average CAP rates that are being paid for comparableproperties in the subject property submarket.

Value Change. The method can calculate the difference between purchaseprice of a building and the sales price of a building.

This calculation is conducted algorithmically using relevant data onsale transactions, such as but not limited to: 1) occupancy at the timeof purchase, 2) occupancy at the time of sale, 3) available NetOperating Income (NOI) at the time of purchase, which is utilized in theCAP rate calculation, 4) the NOI at the time of sale, which is the CAPrate on a sale, 5) all financing information that can be gathered forfinancing placed on the property at the time of purchase, 6) allfinancing information that can be gathered for financing placed on theproperty at the time of sale, although this data point is more importantto the system's historical record keeping used for future analytics ofthe property investment sales marketplace, and 7) additional financingplaced on the property during the term of ownership, such as mezzanineloans or refinancings. The algorithm is regularly adjusted based on theregular collection of data and may be adjusted via machine learning.

Any of the seven itemized information types can be visualized uniquelyor in a group and compared to peer buildings using, for example, a colorscale range applied to the reality mesh, facilitated by the storedcoordinate data.

Determining the equity in a property transaction may be conducted bycalculating the purchase price minus the debt placed at time ofpurchase. This equals the equity invested in a transaction. At the timeof sale, the sales price minus the debt balance retired upon sale equalsthe profit or loss. By calculating the difference between originalequity invested and the net profit after repayment of existing debt atthe time of sale, calculations can be made to determine the equitymultiple and internal rate of return (IRR) which are important metricsto investors.

This value change can be visualized by the system for any individualbuilding or multiple buildings represented within the reality mesh.

Real Estate Industry Outputs. The physical and financial attribute dataof a building are very important to real estate transactions. Buildingparameters such as ceiling heights, floor-to-ceiling windows, columnspacing, loss factor, curtain wall type, floorplate size, etc., all ofwhich come into play when determining fair market value.

These attributes, all or some of which are organized and staged forspecific visualizations, can be outputs via overlay in a display toconvey specific information to various consumers of the information.Possible outputs include development, finance, residential, and officespace. An example of a financial output would be a visualization ofexisting loan size, terms, date of origination and maturity, and lendertype (debt fund, sovereign wealth fund, regional or national bank). Thiscan be used to visualize buildings that have high debt to value ratiosthat have a higher probability of mortgage defaults. This is a tool inthe system of the present invention that users can use to sort throughthe marketplace and highlight a set of buildings that meet the criteriaof being leveraged beyond a particular point set by the user. Users canuse this tool to identify buildings that are under financial stress bytheir loan to value ratio. Buildings that carry mortgages in amountsthat are close to exceeding the ability of the properties rental yieldto pay the monthly mortgage payments are financially stressed. Thisvisualization would utilize the coordinates created to stylize thereality mesh to present the output values for a single building ormultiple buildings using, as an example, a comparative color range. Thesystem also considers the passing of time and can change the outputvisualization based on a user inputted time range or future date.

Similarly, anticipated growth (or decline) in value, based on the datain the database, is determinable and may be visualized as well.

Over time this data will become a predictor of financial performance asthe correlation of physical attributes and asset performance data becomemore robust. Certain physical attributes such as column spacing andcurtain wall (e.g., floor to ceiling glass, masonry, punchout) can behighlighted directly on the buildings in the reality mesh with greatprecision because those attributes are represented across the surface ofthe building and are visible in the textures of the mesh. This allows auser to query the system to return, for example, a representation of allbuildings in a submarket with highlighting applied to buildings withcolumn spacings of a specific range and to see those results returnedwith the precise columns at accurate spacings projected on the actualbuildings in the mesh that meet the search criteria. Additionally, oncethis data is returned and available in the user interface, the attributemetadata becomes available, such as the type of glass in windows,insulation factors, installation costs, replacement costs andcombination queries with government data also become possible such asfaçade inspection dates (enforced by law in NYC), HVAC equipmentinspection dates (testing for bacteria in water coolers/chillers in NYCis a legal requirement), and water tower testing, which is mandated inNew York City. Additionally, the system can also allow users to sort andhighlight buildings that contain mechanical equipment such as HVACsystems, elevator and escalator systems, rooftop chillers, etc., thatwere installed or serviced since a date set by the user. This allows theuser to identify buildings with end of life mechanical, life safety, airhandling, electrical, internet connectivity and utility systems, thestate of which impact a property's valuation. Example users of thisfunctionality would include building owners and vendors of mechanical,life safety, air handling, electrical and utility systems. Visualizingdata in this manner provides immediate evidence of non-compliance,inspection irregularities and safety risks.

Telecommunications or wireless radio signal strength (includingtelevision signals) surveys are usable by and greatly assisted by thesystem of the present invention because the stored coordinate datacontaining information on building materials allows thethree-dimensional modelling of signal propagation throughout a denseurban area consisting of concrete, steel, and glass structures, andillustrates areas of weak signal strength in dense areas or areaswithout line-of-site to cellular transmission infrastructure.

Available building power (watts per square foot), backup powergenerators, green roofs, rooftop solar panels, and rooftop solarpotential are also examples of unique infrastructure in a building thatcan be visualized by the system. City governments are contemporaneouslylegislating to reduce C02 and C02 equivalent emissions, minimize theimpact of emissions, and maximize alternative energy generation.Determining the coordinates of these building features and storing thedata relationally is facilitated through the process.

Because the system contains a reality mesh that has captured the stateof the building infrastructure at a single point in time, it can detectchanges to the urban fabric when a refresh of the reality mesh isperformed with more recently captured photogrammetry. This type ofdetection is enabled at least in part by the stored coordinate data. Forexample, new buildings and expansions will become obvious because theywill exist beyond the system's core coordinate domain and become veryevident, allowing for automatic identification, and updating within thesystem.

Predictive Analytics. The methods of the present invention storestransactional data on the purchase, sale and leasing of properties ofvarious types, such as office buildings, apartment buildings, retailbuildings, office and residential condominium as well as co-op units,hotels, land-lease buildings, parking and industrial buildings. Eachtransaction record contains attributes such as, but not limited to,purchaser, seller, cap rate, submarket, broker of either party, saleprice, sale date, building class, building area, property dimensions,year built, years renovated, tenant information, vacancy information,hotel occupancy information, operating income, operating costs, lastsale price, length of ownership, flood plain risk, curtain wall type,existing debt, existing loan-terms, loan size, lender, and lender type.

The system can aggregate the per square foot pricing for individualtransactions or average per square foot pricing for specific types ofproperties in the general market, any specific submarket, or acompetitive set of properties.

By examining the transactional data and by organizing it by attribute,the system of the present invention can identify patterns, correlations,and anomalies, but only if the data is first visualized using thesystem's core reality mesh coordinate data. That is, the is system ofthe present invention can analyze the visualization and achieveconclusions. The methods of the present invention include an interfacethat allows the user to selectively choose different transactionalattributes and cycle through various combinations to producevisualizations that reveal import factors in determining marketvaluation. Here are several examples of these economic questions:

Example 1: of three office buildings purchased in the same year and thensold in 2011, why did building X increase in value by a multiple of 3when property Y increased in value only by a multiple of 2? The systemof the present invention presents a user interface allowing theattributes of these transactions to be highlighted independently. Thesystem can also draw a colorized (or otherwise distinguishable)wireframe polygon around a three-dimensional representation of thebuilding in the reality mesh to show a second information graphicvariable in context upon the highlighted mesh. By iteratingvisualizations of the various transactional attributes, the user (or thesystem of the present invention) can algorithmically identify whichattribute is responsible for the difference in valuation betweenbuilding X and Y. Again, these algorithms can automatedly be adjustedbased on on-going data collection (e.g., implementing machine learningtoward revising one or more algorithms).

Importantly, when colorization is discussed, it is important torecognize that the color selections preferably could be based onspectrum ranges, for example, reflecting expected minimum and maximumvalues or another stylistic treatment could be used such as opacity orarea tinting, similar to the previously described “fog” effect. Colorselections by range might involve use of multiple colors where, forexample, red is a “high” range and blue is a “low” range, with othercolors used in between.

Example 2: from a selection of residential condominium transactions inthe same year, the properties with the highest per square foot saleprices can be identified and the concentrations identified in a specificbuilding or submarkets or within a city. The system uses building IDsand unit numbers of condominiums transacted and color codes (orotherwise distinguishes) the sale prices on a gradient. The coordinatesassociated with the selected IDs are projected on the mesh andhighlighted units reveal the pattern.

Although color gradients are generally used as the primary indicator toreveal information, buildings and units that are returned in queryresults can also be indicated with other screen drawing elements such aslines, labels, or graphs, such as meters and gauges, that are drawnexterior to the building in the mesh but in context to the subjectsub-market, unit, floor, or building. For example the system can float adollar symbol in space beside a unit and colorize the dollar symbol asan indication of value change, green for an increase in value or red fora loss.

Example 3: by analyzing the operating costs of various buildingstransacted during the same year the user or system can breakdown thiscollection of costs to specific line items such as real estate taxes,property insurance, repairs and maintenance, cleaning and janitorial,payroll and security, heating fuel, electric, water and sewer,management fees and administrative fees. Values for each of thesevariables can be charted and displayed, such as on a color spectrum, andprojected using the coordinates throughout the reality mesh to revealinsights and act as an efficient business intelligence module within thesystem. Users can create subsets of buildings to compare operatingexpense costs to determine average costs and identify where expensescould be reduced or reasons for the differences in cost.

Example 4: analyzing attributes of property transactions with differenttypes of curtain walls is an important comparative physical buildingfeature that can be visualized in the context of the present invention.The present invention maintains records of the type of non-structuralouter covering such as glass panels, metal panels, floor to ceilingwindows, masonry, or punchout style walls. This is an important factorin the valuation of a property. Because the system's database containsrecords of property transactions attributed with masonry curtain wallstransacting at price X, the system of the present invention can be usedto predict valuation change of the property if the curtain walls arereplaced with floor to ceiling windows by using the comparative valuedifference of the transactions for similar buildings with floor toceiling windows. By extension, a similar valuation change analysis canbe performed using other physical attributes such as HVAC equipmentupgrades or additions and/or renovations to unique infrastructure suchas life safety, telecom, pools, health clubs, porte-cocheres, parking,roof deck, or a change to the elevator ratio per square foot of space.Effectively, each property type has different attributes that correlateto value.

The predictive analytics of the present invention can also leverage thesystem's archive of historical leasing, rental, hotel room rates andbuilding mechanical systems such as generators, HVAC equipment, boilers,elevator systems, and shared conference facilities. This includes officeand retail leasing, residential apartment rentals, and hotel roombooking. Hotel booking data can be analyzed by date and presented with atime-based animation to identify the months of the year that fetch thehighest hotel booking rates per door, or room. Hotel booking data canalso be presented in real-time with a feed from a private hotel bookingAPI such as Expedia's to show the current asking rates per room for auser selected date or date range. Residential apartment rental data andcondominium per square foot sales pricing can be similarly analyzed tofind seasonal changes in rental rates. To do this, the system presentsthe user with a GUI that allows, for example, hotel booking data in oneor more submarket of a city, to be colorized on a gradient scale, byspecific hotel room with precise room (or unit) coordinates, used by theGUI to highlight the reality mesh. The interface allows a user tocontrol a time-based animation where building, floor, and unithighlighting turns on and off by playing and pausing the presentationover time based on any of the date values in the database, such ascommercial rents, leasing activity, tenant data, residential rentals,hotel booking records or any of the attributes listed in the paragraphbelow.

The system analyzes historical rents achieved at all buildings and bycomparing the rents achieve against physical and operational attributesa correlation will be apparent. The following list comprises some of thevariable that influence the rents buildings achieve: views, floor toceiling windows vs punch out windows, ceiling heights, buildingamenities (shared conference rooms, cafeterias, building gym, bicyclestorage, meeting facilities, parking), building measurement standards,column spacing, proximity to public transportation, building age, dateof last renovation, back-up power, rental concession package, tenantimprovement allowance, lease terms (length, options to expand, contractor break the lease), large contiguous blocks of space leases vs smallspaces, operating expenses, real estate taxes, general real estatemarket performance, and specific submarket real estate performance, toname a few. Certain buildings outperform the market and theircompetitive set. It is often a combination of some of the is keyvariables listed above that result in a property being to achievepremium rents. By tracking the multiple physical and operationalvariables the system will identify the ones that result in higher rentsand allow for greater predictability.

The analytics module can also use the coordinate highlighting system tofuture project property valuations based on changes in cap rate. Acapitalization rate is defined as a comparative valuation metric forproperties with income and is measured as the net operating incomedivided by purchase price which effectively is the return an investorwill receive on the purchase price. The system interface allows the userto adjust the capitalization rate for a property at a point in thefuture and project the valuation and valuation change from the previoussale date using the coordinate highlighting system as a visualindicator. A user can select types of properties by class in certainsubmarkets to refine the results and provide an explanatory narrativefor an audience using these analytics to study cap rate compression orexpansion trends in a commercial real estate market.

The system can present all or a pre-selection of the application datavisualizations, including all of the analytics visualizations, asautomated presentations that are “canned” based on the user role andplay these slides to a user at regular intervals with current data. Forexample, as a user on the system, an office leasing agent can play theslides relevant to changes in the office leasing market in a submarketor across the entire city and quickly become knowledgeable about anymajor market changes. Similarly, a residential rental agent can play therelevant slides in the graphical user interface that address currentresidential rental activity and see the data that is impacting currentrental rates, vacancy levels and current market inventory. Thesevisualizations, presented in slide format, can be distributed by usersof the system as unique URLs, sent in emails or text message, to showtheir clients or colleagues to communicate market conditions in a timeefficient manner.

Data Sources. The system consumes data from three primary sources (A, B,C below), it preferably does not utilize any traditional GIS data suchas shapefiles, cadastral maps, street maps, available from government orprivate sources in an unaltered form. The present invention synchronizesreceived data for storage. Municipally sourced property and buildingfootprint files containing unique identifiers are the only external datasource used to identify properties, however the process worksindependently of any government or third party supplied propertyboundary data.

The process of synchronization begins by importing a table of spatialand physical property attributes from a city, county, state, or federalgovernment source and uses it to relate volumetric regions of thereality mesh with a government common identifying number (ID). This IDis used to structure database queries against the public record set. Forexample, once a government's unique property identifier code isassociated with a volumetric region within the reality mesh, that regioncan be stylized, manipulated, hidden, emphasized, used to show data incontext and/or related to spatially, or thematically like charts andgraphs. Further, character symbols can be used to be drawn in proximityto the relevant region of the mesh creating the impression of metersthat can be static or animated displaying data with time variables suchas energy or water consumption, emissions and exhausts, or financialinformation such as mortgage details, debt, net operating income, ortenancy. See FIG. 21 for example. This technique improves the system'scapacity to convey information quickly.

There is a reference in FIG. 21 to a building centroid; this is definedas the coordinate point at the approximate center of a building floor.This coordinate point is derivable from either an adjusted buildingfootprints or a coordinate selection from the coordinate bed in FIG. 1 .The meters that are illustrated in FIG. 21 can therefore be drawnrelationally to the building centroid allowing for the correct visualcontext for meters that reveal property information. Meters canrepresent a scale of data such as energy, water or carbon dioxideequivalent emissions, debt levels or any property variable that is bestunderstood depicted with a color spectrum range.

A) Manually Adjusted, Traditional GIS Files

Every unique building footprint has its vertices (coordinate points)adjusted to match the mesh. This is performed by adjusting sourcecoordinates to match the visual representation of the property,including land boundaries, within the reality mesh. This is accomplishedby seeing the updated altitude of the polygon control surface, asillustrated in FIG. 22 , change as user alters position parameters andthen traps the updated coordinates.

It is important to note that government footprint GIS datums aretypically sourced from cadastral maps that are not precise, real worldcoordinate representations of reality. The system's photogrammetrymodels, when calibrated on the cartesian map, are precise, real worlddatasets that can have coordinates extracted that will be accurate inthe real world. This difference requires every government GIS footprintto be slightly adjusted at the vertices to match the photogrammetricmesh. This process is performed manually using various software toolsthat allow a user to select a vertex or is edge and adjust its latitude,longitude, altitude or any combination of those parameters. This processis necessary at the floor level, allowing the system to supportbuildings with different floor to ceiling heights throughout differentfloor ranges. This manual process is necessary for every floor in everybuilding in the system, an example of one of the software tools used inthe process is represented in FIG. 22 .

B) Manually Selected Mesh Coordinates

The system of the present invention consumes coordinates that aredirectly selected from the reality mesh to create property coordinatesfor new properties and new or renovated buildings that have beenconstructed and do not yet exist in government records. The system cantrap any coordinates from a picked selection anywhere on the mesh andassociate the selection with a new system building ID. A minimum ofthree unique coordinate pairs is necessary to properly assemble atwo-dimensional polygon that will match a property representation in thereality mesh. This same technique is used to classify buildingmechanical equipment such as rooftop drinking water tanks, coolingtowers, HVAC and air handling equipment, cellular and radio transmissioninfrastructure, security cameras, solar panels and solar panellocations, air venting and exhaust systems, and elevator systems.Architectural and landscape features such as building entry and egressareas, security zones, parking areas, rooftop gardens, façade safety andproperty landscaping can also be identified by the selected meshcoordinates and be associated with the unique identifier for theproperty.

C) Real Estate Information

The system of the present invention consumes various types of documentsand associates them with the system's unique property identifies.Examples of document types: structured tables, Microsoft Excel files,CSV files, Argus models, text documents, PDF files, JPEG images, PNGimages, floorplan layout files and other metadata necessary and orrelated to property transactions and building management.

Examples of document content include: commercial and residential leaseand sub-lease agreements, property budgets and operating costs, propertyownership legal structures (i.e., condominium, cooperative, jointownership, freehold), building covenants, condominium plans, rent rolls,mortgage documents, financial records and agreements, deeds, taxrecords, development or air rights, market real estate transactions,certificates of occupancy, insurance documents, municipal assessments,environmental assessment reports, flood and other natural risk datacollected for insurance purposes, planning laws, planning policies, citylaws, city policies, public health surveys, air quality surveys, and anyother publicly or privately available documents containing informationrelevant to real estate properties in the system.

The system of the present invention can create associated documents,which may be displayed as well. Each document is associated with aproperty using various software tools. These documents are assimilatedinto the system as tables of data or stored as binary large objects inthe database, associated with unique property identifiers. Also, somedocuments are stored on the file system, or database, of the presentinvention in folder names containing the unique property identifiersfrom the system.

The system also needs to know the elevation of the top floor ofoccupiable space in a building to correctly highlight floors. This isdone with the system's Building Altitude is form which allows us to setunique floor heights for every floor to properly match the building.Various sources of information can be used to accomplish this, as wellas examining the façade and window spacings obtained from somecombination of overhead and public and private sources.

This information is refined as the system obtains slab heightmeasurements from owners.

Residential and commercial units are created in the system's augmentedreality approach from the floor coordinates using the “Create Partials”creation process. These are forms that allow us to select the exteriorpoints on a façade where units are divided along a floor. This form isalso used to map a rasterized floorplan drawing to a full or partialfloor so that the system can show the floorplan in-situ, with regions ofthe mesh above the subject unit clipped to reveal the floorplan.

These coordinates may need to undergo manual calibration to fit thebuildings in a reality mesh because they come from traditional cadastralmaps, which are recordings of the dimensions and location of landparcels. However, when these coordinates do not precisely match realityand they need to have the vertices adjusted by a user to perfectly matchthe photogrammetric reality mesh.

The system contains the necessary logic to allow a user to select thecoordinates of rooftop infrastructure (cooling towers, water tanks,cellular equipment, solar panels, etc.) from the system's corefootprints dataset and create an association in the system's database,which may alternatively be done automatically. Because the systemalready has a database relationship with the building IDs and the uniqueproperty ID issued by the city, it can stylize the highlight applied tothe subject infrastructure with available city is open data. Forexample, water tanks that have failed health inspections can behighlighted in red.

In order for a user to select a parameter (or more than one) fordisplay, there are several available approaches. In addition toclickable entries as part of a graphical user interface, clickable menuscan appear on an associated portion of the graphical user interface,where the menus can vary based on previous selections or can becustomized to the type of user (e.g., real estate professional vs.average consumer). Further, such selection can be voice activated tospeed the process. Positive responses to selections can be color codedor otherwise displayed based on attributes of the selection (such asprice range or greenhouse gas emission ranges).

Additionally, the GUI information display boxes (information boxes) thatare presented to the user when they click on any highlighted securitycamera or rooftop infrastructure are connected by a thin red line, drawnon screen in context with the application interface, connecting thecentroid (central spatial coordinate) of the selected infrastructure andthe corner of the infobox of the GUI. This line remains affixed to theon-screen infobox, while the virtual globe (which is a conventionalsatellite or rasterized city or road map, also known as a basemap,projected on a spherical user interface) camera moves, maintaining adirect indicator between the infobox and the location of the realitymesh containing the selected infrastructure. This is useful because itcreates an immediately clear description of equipment information,condition and geolocation with current government data.

Coding approach to the present invention: The system uses a traditionalLAMP-stack (Linux, Apache, MySQL, PHP) web service that uses opensourcecode for the operating system (Linux, GPL), web server (Apache, Apache2.0 license), database (MySQL, GPL) and virtual globe (CesiumJS, Apache2.0). There are various open source virtual globes available, such asNASA World Wind, osgEarth, ossim Planet, CesiumJS, gvSIG 3D and KDEMarble. The system presently uses the open source CesiumJS because ofits versatility with different reality mesh tileset formats.

All of the middle ware or application-level code used is proprietary.Open source code has been used for some graphical user interfacecomponents and the virtual globe which is licensed under Apache 2.0.There are no proprietary modifications made to the generic hostingservice, filesystem or Linux OS, however the system's database schemacontains many proprietary designs and information.

FIG. 23 describes an example workflow of data during a typical usersession. On the front-end client side of the application, the user ispresented with a graphical user interface that is a reality mesh of anurban area. Typically, the first filter of interest is to narrowgeography, so Submarket is presented to the user and they makeselection. Query is sent to the database to select values needed toposition the camera in the GIS or virtual globe. These values includelongitude, latitude, altitude, heading, tilt, pitch and roll. Oncereturned to the GUI from the DB the values move the camera to bepositioned over the correct submarket. For example, Financial District,and the camera is focused on the area North East of Battery Park inManhattan.

The next step in the diagram is a selection of A-class buildings. Thissearch is structured as a query and sent to the database to returncoordinates for all A-class buildings. The returned data will consist ofa large quantity of coordinate strings representing the spatialboundaries of the properties in the reality mesh. The user will see theA-class buildings all highlight to a preselected color.

Another selection is made to request the available space for lease orrent in the buildings from the previous result set of A-class buildings.This query returns floor level coordinates which are stylized toprecisely highlight full floors or partial floors or units with the meshusing volumetric highlighting technique.

FIG. 24 depicts the Application Infrastructure Customization of thepresent invention.

This figure describes the level of customization required for eachinfrastructure component of the application. Complete indicates thecomponent has been entirely created for the system and the various otherpatterns indicate reduced level of customization effort required tosetup the system.

The basemap (the conventional satellite or city or road map overlaid onthe virtual sphere in a GIS) contains public and private sources ofterrain imagery exclusive of the mesh. They are not used by theapplication but provide location context for the mesh from highelevation. For example, the system's reality mesh example coversdowntown Manhattan from Canal Street to the Battery. The area North ofCanal Street is represented by the basemap which the reality mesh ispositioned within spatially. Public imagery providers for basemapsinclude NASA and OpenStreetMap. Private imagery providers, accessiblewith application programming interface (API) keys, include Esri, Bingand Mapbox.

FIG. 25 depicts Application Infrastructure for Web. This figure showshow the application is configured to run in a standard web hostingdesign with a remote webserver located in a virtualized cloudenvironment (e.g., AWS) accessible over the public internet. Thevirtualized server runs on Linux and has a file system, database andwebserver, each a component necessary for the application to run. Thefile system contains the reality mesh tileset files, virtual globemapping software, customized JavaScript and php files to run the clientapplication from a web browser. Supported web browsers are all thatsupport the HTML5 WebGL standard, which is common. The virtualizedserver also contains the open source MySQL database, and opensource webserver software Apache.

FIG. 26 depicts Application Infrastructure iPad Standalone. This figureshows the application configured to run on an iPad as a packagedapplication with no direct internet connection. This involves usingApple's XCode programming application to create a package of theweb-delivered version of the system's graphical user interface, realitymesh and data. This figure illustrates how that standalone applicationis configured, not how the package is built in XCode. The package isdescribed by the items in the largest box. The application must be sideloaded (transferred directly to the tablet via cable from a PC insteadof distributed through a cloud-based application store) to the tabletbecause of the large file size of the mesh, which encounters limitscreated by online application delivery methods such as Google Play orApple's Appstore.

The standalone application uses the same JavaScript/PHP front endclient, as well as CesiumJS opensource virtual globe and web server.However instead of a local connection to a database the application usesclient-side JSON data files containing all possible coordinate datanecessary to generate visualizations within the reality mesh. Thereality mesh tileset files are also stored as part of the package. Thisresults in faster mesh loading times because the mesh is notbottlenecked by potentially slow internet connections.

FIG. 27 , Fog effect. This figure illustrates a submarket selected inlower Manhattan by applying a fog effect to unselected area. This makesthe highlighted buildings in the selected market (World Trade Centre)more prominent and aids in comprehending the visualization. The visual“fog” effect is created by using the system's volumetric highlightingcapability applied to the boundaries of each submarket within thereality mesh.

Fog Grouping Distortion Solution. To solve a visual distortion problemencountered by GIS software that would confuse multiple holes punches inthe fog highlighting (used to emphasize search results) and producepolygon distortions represented as stray vectors drawn to the horizon,the system includes a solution. The problem occurred when two or morebuildings are beside each other in real space and share boundarycoordinates. The solution is to create a set of matrices that join allthe combinations of the building coordinates involved in the distortion.For example, if there are 3 buildings (A, B, C) overlapping each other,a matrix is created with coordinate combinations for each (Aft BC, CA,ABC). Those are the only four possible combinations of buildingsrequiring holes in the fog highlight for 3 buildings. Using the matrix,the system can join building A's and building B's boundaries to use fordefining the hole. Using this approach, the GIS eliminates anydistortions. This technique is used manually in code when distortionsare seen in the GIS. If combination matrix AB and BA are the same, evenif the keys (Aft BA, AC, CA, BC, CB) are different, their outcome is thesame. So those combinations are not used again. The system containsadditional ordering logic to avoid duplicates in a combination matrix.For example, if buildings with unique identifiers 12, 13 and 14 are usedfor fog highlighting, the system always sorts buildings with uniqueidentifiers in ascending order, and then checks the available matrix.This overlapping matrix data stored in the database also has buildingsorganized in this manner. This logic makes it easy for matching.

This functionality is important because it allows the system tovisualize data relative to multiple buildings while draping theremainder of the reality mesh in fog. FIG. 28 illustrates an example ofhow this feature is used by the user interface. Orange and yellowbuildings that represent Condo and Rental type buildings have beenpunched through the fog to provide emphasis.

Inverse Clipping Logic. Using a defined coordinate plane the systemreverses direction of the plane and then switch the view to oppositeplanes to clip all portions of the mesh exclusive of the subjectbuilding. This allows the system to extricate a single building or blockfrom the entire mesh of a city. In doing so the GIS changes positionvalues for the mesh, which requires manual settings for every buildingto achieve this visualization.

This functionality is important because it allows the system to generatebuilding-specific 3D stacking plans without neighboring buildingsinterfering with the view of the subject property. FIG. 29 depicts howthis functionality is used by the user interface to show availablerental units in a single building in Lower Manhattan.

Setting Partials to Match Floorplans. The partial suite coordinatescreated manually by the system to highlight the suite positionexternally on the building in the reality mesh also needs to align withthe dimensions of a floorplan image file (PDF or rasterized image) whenthe mesh is clipped to the specific floor and the image file drawnwithin the bounds of the partial suite coordinates. Using only theinitial set of externally (external to the building in the mesh)captured partial coordinates, the GIS can show an alignment problem withthe rendered floorplan image file when drawn in this manner. Forexample, the image file can be drawn beyond the boundaries of thepartial coordinates and can extend into space from the building in themesh. The solution requires a manual process to select a different setof mesh coordinates from inside of the mesh at the clipped floorposition to precisely match the floorplan. The system solves thisproblem by providing a tool for a user to select (or selected semi orwholly automatedly) a building clipped to a selected floor therebyallowing a user to align the floorplan file to “anchor” coordinates thatrun along an external perimeter of the building in the mesh and thenselect new interior coordinates that match the dimensions of thefloorplan. This is a laborious process (more so for partial floorplansthan full floor floorplans) that requires resizing and rotating an imagefile to match the building floor parameters as well as the parameters ofneighboring floorplans on the same floor that are either beside the unitor on other sides of the same floor. Once these coordinates are trappedand stored in the system they provide the user interface with thenecessary data to draw floors in-situ on a clipped (aka sliced) floor aswell as the Floating Lines and Polygon Fences (later portions of thisdocument) in context with the floors and suites within the buildings ofthe reality mesh.

FIG. 30 depicts the tool used by the system to position floorplans on aclipped floor within a building in the reality mesh. Small yellow dotsact as control points to adjust the image.

Automatic Views Logic. The system can generate views from a specificsuite or unit by calculating the building centroid and partial suitecentroid. The directional vector is determined by the position of thepartial suite centroid in relation to the building centroid on acartesian plane.

The reference to camera is used many times in this document. It refersto how the end user looks at the object (building, reality mesh, slicedfloor, etc.) from an angle, height, distance and rotation. The“direction of camera” reference in the below paragraph can be understoodas a vector representation of a line, from point A to B that defines thedirection when a person standing at point A looks at Point B.

Panoramic views are also generated by the system in a similar manner tosuite or unit views. The system calculates the direction of the camerausing the building centroid and partial centroid. To achieve a panoramiccamera motion a path is required along which the camera will travel. Thestored coordinates for the partial unit are used to create this path,and using the GIS's clock, the system defines clock tick events thattravel the camera from point to point giving the panoramic view. Tocalculate the points, the distance between building centroid and partialsuite centroid is defined as a threshold distance and any other partialcoordinate having a distance from the building centroid greater than thethreshold is utilized for a panoramic view point. As described in FIG.31 , the black square outline represents a building footprint and theblue lines represent the partial unit coordinates. The green coordinatesindicate points having distance greater than the threshold valuecalculated earlier.

This functionality is very important because it gives the user thevisual experience of seeing the real world view through the reality meshof the cityscape from the floor or unit. It also allows the userinterface to quickly travel to the view without the user having tonavigate using the controls of the GIS. Because the views from a unit ina building impact the commercial rents that a unit can fetch on themarket, this is an important feature to understand the economicpotential of a commercial or residential space for sale or rent.

Elevator Cores. Using the stored coordinates of each floor and theheight of the building, the system of the present invention has thenecessary parameters to create a polygon shape that approximates thedimensions of the building elevator core and elevator cars. Thisvisualization can be presented in the user interface with an opacityvalue cast over the reality mesh so that the elevator core appearsthrough the transparent buildings in the mesh. FIG. 32 illustrates thisconcept with a white, opaque polygon drawn inside a building in LowerManhattan.

Because city data can include maintenance, permit and safety informationrelated to elevator equipment this visualization can be useful toidentify upkeep problems or browse through large amounts of specifichardware types and manufacturers of elevator equipment to findparticular information.

Floating Lines. Because the system can manually set partial unitcoordinates it can be used to draw polygons in the space above where afloor has been clipped (cleared) from the reality mesh. By displayingunits in this manner, it allows the user to understand building unitinformation while examining a selected unit's floorplan or other detailsin a residential or commercial building. The user can then selectanother unit based on the shape or altitude of another unit's floorplanwithout having to redraw the mesh and possibly lose spatial context.This improves the awareness of the types of units returned or drawn in asearch query because the user can visually filter the smaller or largerunits that are or are not of interest. FIG. 33 illustrates how these“floating lines” are used by the user interface to present thisinformation.

Floating lines can be stylized using colorized solid or transparentpolygons and include the floorplan imagery files (PDFs or rasterizedimages) within their bounds.

Polygon Fencing Around Partial Units. Similar to the logic for floatinglines, a polygon fence can use the partial unit coordinates (stored inthe system through the process of defining partial units on a floor) todrawn upwards from the plane or surface of a clipped building floor inthe mesh. This polygon fence would show the demarcations of a floor byunits and appear as a vertical filled or outlined wireframe colorized byany multitude of user selected variable, such as the number of bedrooms,rental rate or amount of time available on the market. The polygon fencecould also indicate internal wall materials of abutting suites, the typeof external windows (punchout, floor-to-ceiling).

Adding Rooftop Infrastructure. The system features a manual coordinateselection tool used to identify, describe and store types of rooftopbuilding equipment. For example, the user can select the coordinatebounds around the perimeter on a roof of the cooling tower, add adescription, and then store that real-world infrastructure item in thesystem's database with a unique ID. That ID can then be joined with aquery between the government permit and maintenance records for theselected cooling tower in the relevant building and the user interfacecan then visualize the cooling tower in the reality mesh using any ofthe available parameters (i.e., registration date, capacity, make,model, intended use) as style-setting variables. Types of supportedinfrastructure include air handling units, cellular antennas, chillers,cooling towers, green roofs, roof top units, solar panels, water towers,cranes, and HVAC equipment. Styles include highlight colorization orpolygon lines. When clicked on, the user interface draws a line thatconnects an infobox displaying equipment fields and descriptions to theprecise location of the infrastructure using the centroid point of thestored coordinates.

FIG. 34 illustrates three defined pieces of rooftop infrastructure andthe infobox that details them; cellular antennae, cooling tower andwater tower.

Automated Presentation Outputs. The system has pre-selected slides thatplay a series of visualizations that present overviews and analytics ofthe office leasing and sales market, residential rental and salesmarket, development market, city government open data and tenantindustry concentrations. These automated presentations can be selectedfrom the user interface from a menu of options or sent (emailed) to auser as compartmentalized URLs that play immediately upon opening in theweb browser. The data in the presentation slides reflect the currentgovernment, commercial, real estate and user data stored in the systemdatabase. Each slide plays at a user-set interval and includes a timerthat is displayed before the next slide is played. Each slide can bepaused and interacted with if it includes nested functionality is suchas building camera controls, line indicators (as seen in cellular towermaintenance example in FIG. 35 which depicts line connecting allbuildings with recent cellular maintenance filings from T-MobileNortheast LLC) or building information boxes (windows in the userinterface).

While the invention has been described in detail in connection with onlya limited number of embodiments, it should be readily understood thatthe invention is not limited to the foregoing description.

APPENDIX 1 Appendix 1 Source Agency Category Dataset Description FormatsPropSee Internal Proprietary Lease Expiration CSV, XML, JSON PropSeeInternal Proprietary In Place Rent CSV, XML, JSON PropSee InternalProprietary Vacancy CSV, XML, JSON PropSee Internal Proprietary FloorPlans CSV, XML, JSON PropSee Internal Proprietary Tenants CSV, XML, JSONPropSee Internal Proprietary Portfolios CSV, XML, JSON PropSee InternalProprietary Available Office Space CSV, XML, JSON PropSee InternalProprietary Expense Comparables CSV, XML, JSON PropSee InternalProprietary Residential Sale CSV, XML, JSON Listings PropSee InternalProprietary Residential Rental CSV, XML, JSON Listings PropSee InternalProprietary Residential Rental CSV, XML, JSON Yield PropSee InternalProprietary Residential Investment CSV, XML, JSON Sale Yield PropSeeInternal Proprietary Investor Profiles REIT, Institution, CSV, XML, JSONPrivate, User, Foreign PropSee Internal Proprietary Current InvestmentBy PSF CSV, XML, JSON Sales PropSee Internal Proprietary HistoricalInvestment By PSF CSV, XML, JSON Sales PropSee Internal ProprietaryInvestment Sale Buyer CSV, XML, JSON PropSee Internal ProprietaryInvestment Sale Vendor CSV, XML, JSON PropSee Internal ProprietaryBuyers Broker CSV, XML, JSON PropSee Internal Proprietary Common lenderCSV, XML, JSON PropSee Internal Proprietary Percent increase in CSV,XML, JSON value PropSee Internal Proprietary Length of ownership CSV,XML, JSON PropSee Internal Proprietary Loss factor CSV, XML, JSONPropSee Internal Proprietary Curtain wall Glass, Floor to CSV, XML, JSONceiling, Masonry, Punchout PropSee Internal Proprietary Ceiling heightsCSV, XML, JSON PropSee Internal Proprietary Partial Interest/ CSV, XML,JSON Partnerships PropSee Internal Proprietary Sale Comps CSV, XML, JSONPropSee Internal Proprietary Lease Comps CSV, XML, JSON PropSee InternalProprietary Average rent Submarket, Class, CSV, XML, JSON FloorplateSize, Building Age, Tower vs Base PropSee Internal Proprietary Underdevelopment Total, Submarket, CSV, XML, JSON Delivery, Preleased PropSeeInternal Proprietary Floorplate size From X to Y CSV, XML, JSON PropSeeInternal Proprietary Desired vacancy CSV, XML, JSON PropSee InternalProprietary Year of purchase CSV, XML, JSON PropSee Internal ProprietaryAvailability Blocks of space, CSV, XML, JSON asking rent/each space,term PropSee Internal Proprietary Leasehold CSV, XML, JSON PropSeeInternal Proprietary Fee simple CSV, XML, JSON PropSee InternalProprietary Number of tenants CSV, XML, JSON PropSee InternalProprietary Unique CSV, XML, JSON infrastructure PropSee InternalProprietary Co-working tenancy CSV, XML, JSON PropSee InternalProprietary Non-sellers CSV, XML, JSON PropSee Internal ProprietaryVirtual tours CSV, XML, JSON PropSee Internal Proprietary Vieworientation CSV, XML, JSON PropSee Internal Proprietary RetailHigh-value, current CSV, XML, JSON available, leased but dark PropSeeInternal Proprietary On the market & how CSV, XML, JSON long PropSeeInternal Proprietary Selling agent CSV, XML, JSON PropSee InternalProprietary Leasing agent CSV, XML, JSON PropSee Internal ProprietaryManaging agent CSV, XML, JSON PropSee Internal Proprietary BuildingClass CSV, XML, JSON PropSee Internal Proprietary Building Size CSV,XML, JSON PropSee Internal Proprietary Building Grossup CSV, XML, JSONRate PropSee Internal Proprietary Asking Rent CSV, XML, JSON PropSeeInternal Proprietary Loan Size CSV, XML, JSON PropSee InternalProprietary Loan by borrower CSV, XML, JSON PropSee Internal ProprietaryCross CSV, XML, JSON collateralization PropSee Internal Proprietary CMBSCSV, XML, JSON PropSee Internal Proprietary Mezzanine loan(s) CSV, XML,JSON PropSee Internal Proprietary Preferred equity CSV, XML, JSONPropSee Internal Proprietary Mortgage broker CSV, XML, JSON PropSeeInternal Proprietary Lender CSV, XML, JSON PropSee Internal ProprietaryLender type Debt fund, Foreign, CSV, XML, JSON Regional bank, Nationalbank PropSee Internal Proprietary Existing loan-terms CSV, XML, JSONPropSee Internal Proprietary Borrower entity History, credit CSV, XML,JSON score PropSee Internal Proprietary Loan by date of CSV, XML, JSONorigination PropSee Internal Proprietary Loan by date of CSV, XML, JSONmaturity PropSee Internal Proprietary Loan ratios LTV or LTC CSV, XML,JSON PropSee Internal Proprietary Debt maturity CSV, XML, JSON PropSeeInternal Proprietary Appraised value CSV, XML, JSON PropSee InternalProprietary Proximity to subway CSV, XML, JSON PropSee InternalProprietary Number of units CSV, XML, JSON PropSee Internal ProprietaryExistance of 13th CSV, XML, JSON Floor PropSee Internal ProprietaryMissing floors CSV, XML, JSON PropSee Internal CORE Floor height CSV,XML, JSON PropSee Internal CORE Spatial coords for CSV, XML, JSON floorsPropSee Internal CORE Spatial coords for CSV, XML, JSON buildingcentroid PropSee Internal CORE Spatial coords for CSV, XML, JSON unitsPropSee Internal CORE Spatial coords for CSV, XML, JSON unit viewPropSee Internal CORE Spatial coords for CSV, XML, JSON unit viewpanorama PropSee Internal CORE Spatial coords for CSV, XML, JSONentrance PropSee Internal CORE Spatial coords for CSV, XML, JSON egressExpedia Expedia Hotels Hotel vacancy CSV, XML, JSON API Expedia ExpediaHotels Hotel room asking CSV, XML, JSON API price Expedia Expedia HotelsHotel room CSV, XML, JSON API availability City DOF City Government Yearof renovation As found in Property CSV, XML, JSON Land Use Tax lotOutput (PLUTO) City DOF City Government Cooperatives CSV, XML, JSON CityDOB City Government Building Age CSV, XML, JSON City DOITT SocialServices 311 CSV, XML, JSON City DOB Housing & Footprints CSV, XML, JSONDevelopment City DOB Housing & Cellular Antenna CSV, XML, JSONDevelopment Filing City DCAS Housing & Integrated Property Owned andleased by CSV, XML, JSON Development Information System City of New YorkCity DOE Education K-12 Schools CSV, XML, JSON City DOB Health Hospitalsand clinics CSV, XML, JSON City DCP City Government Facilities by CSV,XML, JSON department City DOB Housing & Complaints CSV, XML, JSONDevelopment City MOS Mayor's Office of Energy and Water CSV, XML, JSONSustainabil

Consumption City LPC Housing & Landmarks CSV, XML, JSON Development CityDEP Environment Asbestos Abatement CSV, XML, JSON Jobs City DOB Housing& Permit Issuance CSV, XML, JSON Development City DOB Housing & JobApplication Filing CSV, XML, JSON Development City DOB Housing & FacadeCompliance CSV, XML, JSON Development Safety City DOB Housing &Violations CSV, XML, JSON Development City DSNY Department of GraffitiTracking CSV, XML, JSON Sanitation City MOS Mayor's Office of OccupancyCSV, XML, JSON Sustainabil

City DOI City Government Evictions CSV, XML, JSON City DOB Housing &Stalled Construction CSV, XML, JSON Development Sites City DOB Housing &Certificates of CSV, XML, JSON Development Occupancy City DCP CityGovernment Foreign Government CSV, XML, JSON Ownership City DCP CityGovernment Floor Area Ratio CSV, XML, JSON City DOF City GovernmentACRIS Real Property CSV, XML, JSON City DOF City Government ACRISParties CSV, XML, JSON City DOF City Government ACRIS Personal CSV, XML,JSON City DOHMH Health Restaurant Inspections CSV, XML, JSON City DOHMHHealth Indoor Environmental CSV, XML, JSON Complaints City DOHMH HealthRooftop Water Tank CSV, XML, JSON Inspections City DOHMH Health RodentInspections CSV, XML, JSON City HPD Housing & Maintenance Code CSV, XML,JSON Development Complaints City HPD Housing & Maintenance Code CSV,XML, JSON Development Violations City HPD Health Bedbugs CSV, XML, JSONCity HPD Health Flease CSV, XML, JSON City HPD Health Flies CSV, XML,JSON City HPD Health Mice CSV, XML, JSON City HPD Health Roaches CSV,XML, JSON City HPD Health Termites CSV, XML, JSON City HPD Health Pests(other) CSV, XML, JSON City NYPD Police NYPD Arrests CSV, XML, JSON(Historic) City NYPD Police NYPD Complaints CSV, XML, JSON (Historic)City NYPD Police NYPD Open Cases CSV, XML, JSON City FDNY Fire Dept FDNYCompany Coverage CSV, XML, JSON City FDNY Fire Dept Certificates ofFitness CSV, XML, JSON City FDNY Fire Dept Violation Orders CSV, XML,JSON City FDNY Fire Dept Notice of Violations CSV, XML, JSON City FDNYFire Dept Permit Accounts CSV, XML, JSON City FDNY Fire Dept Letters ofApproval CSV, XML, JSON City DOF Housing & Condo Tax Lots CSV, XML, JSONDevelopment City DOF Housing & Property Tax CSV, XML, JSON DevelopmentCity DOF Housing & Property Tax (Historic) CSV, XML, JSON DevelopmentCity DOF Housing & Assessment CSV, XML, JSON Development City DOFHousing & Hotels CSV, XML, JSON Development City DOF Housing & Sales(Historic) CSV, XML, JSON Development City DOF Housing & Tax Lien SaleLists CSV, XML, JSON Development City DOF Housing & Tax Exemptions CSV,XML, JSON Development City DOF Housing & Tax Abatements CSV, XML, JSONDevelopment City DOF Housing & Condo Income CSV, XML, JSON DevelopmentComparable City SBS Environment Hurricane Sandy CSV, XML, JSONInundation City DCP Public Safety Hurricane Evacuation CSV, XML, JSONZones City DOB Housing & Elevator Device CSV, XML, JSON DevelopmentDetails City DOB Housing & Elevator Permit CSV, XML, JSON DevelopmentApplications City DOB Housing & Boiler Data CSV, XML, JSON DevelopmentCity DCAS Environment Con Edison Steam CSV, XML, JSON Network City DOHMHHealth Rooftop Cooling Tower CSV, XML, JSON City DCP City GovernmentSchool District CSV, XML, JSON City DCP City Government Fire CompanyCSV, XML, JSON City DCP City Government Police Precinct CSV, XML, JSONCity DCP City Government Health Area CSV, XML, JSON City DCP CityGovernment Sanitation Subsection CSV, XML, JSON City DCP City GovernmentCouncil CSV, XML, JSON City MTA Metropolitan MTA Network i.e. New YorkCity CSV, XML, JSON Transit Transit, Long Island Authority Rail Road,Metro- North Railroad City MTA Metropolitan MTA Bridges and ColladaTransit Tunnels. Authority State DHCR Division Rent Regulation Data CSV,XML, JSON Housing and Community Renewal State Attorney Real Estate CondoPlans CSV, XML, JSON General Finance Bureau PropSee Internal ProprietarySubway Station Models Collada PropSee Internal Proprietary NewDevelopment Models Collada PropSee Internal CORE Spatial camera settingi.e. Longitude, CSV, XML, JSON Latitude, Altitude, Heading, Tilt, Pitch,Roll PropSee Internal CORE Highest elevation of Altitude CSV, XML, JSONmarketable space Private Corporate Landlord, or Enterprise datasetSimilar to PropSee CSV, XML, JSON other real data parameters or estateindustry other property data company Private Corporate Landlord, orEnterprise dataset Similar to PropSee Collada other real data parametersor estate industry other property data company Public Public Commonlyknown Submarket Names and i.e. Tribeca, FiDi, Terms Domain areas ofBoundaries Plaza District, geographic Hudson Yards, Murray importanceHill Public Public Commonly known Submarket Names and i.e. Tribeca,FiDi, Terms Domain areas of Boundaries Plaza District, geographic HudsonYards, Murray importance Hill Uses System Highest Parent andVisualization Typical Source Export Rows Fields Method Level Vis LevelPropSee Yes Floor Floor PropSee Yes Floor Floor PropSee Yes FloorBuilding PropSee Yes Floor Floor PropSee Yes Floor Floor PropSee YesBuilding Building PropSee Yes Floor Floor PropSee Yes Floor BuildingPropSee Yes Unit Unit PropSee Yes Unit Unit PropSee Yes Unit UnitPropSee Yes Unit Unit PropSee Yes Unit Building PropSee Yes UnitBuilding PropSee Yes Unit Building PropSee Yes Unit Building PropSee YesUnit Building PropSee Yes Unit Building PropSee Yes Unit BuildingPropSee Yes Unit Building PropSee Yes Unit Building PropSee Yes UnitBuilding PropSee Yes Unit Building PropSee Yes Unit Building PropSee YesUnit Building PropSee Yes Unit Building PropSee Yes Unit BuildingPropSee Yes Unit Building PropSee Yes Building Building PropSee YesFloor Building PropSee Yes Building Building PropSee Yes Unit BuildingPropSee Yes Unit Floor PropSee Yes Unit Building PropSee Yes BuildingBuilding PropSee Yes Building Building PropSee Yes Building BuildingPropSee Yes Building Building PropSee Yes Building Building PropSee YesUnit Unit PropSee Ye Unit Unit PropSee Yes Unit Unit PropSee Yes UnitUnit PropSee Yes Unit Building PropSee Yes Unit Building PropSee YesUnit Building PropSee Yes Building Building PropSee Yes BuildingBuilding PropSee Yes Building Building PropSee Yes Unit Building PropSeeYes Unit Building PropSee Yes Unit Building PropSee Yes Unit BuildingPropSee Yes Unit Building PropSee Yes Unit Building PropSee Yes UnitBuilding PropSee Yes Unit Building PropSee Yes Unit Building PropSee YesUnit Building PropSee Yes Unit Building PropSee Yes Unit BuildingPropSee Yes Unit Building PropSee Yes Unit Building PropSee Yes UnitBuilding PropSee Yes Unit Building PropSee Yes Unit Building PropSee YesFloor Building PropSee Yes Floor Floor PropSee Yes Building BuildingPropSee Yes Building Building PropSee Yes Floor Floor PropSee Yes FloorFloor PropSee Yes Building Building PropSee Yes Unit Unit PropSee YesUnit Unit PropSee Yes Unit Unit PropSee Yes Unit Unit PropSee Yes UnitUnit Expedia Yes Building Building Expedia Yes Building Building ExpediaYes Building Building City PLUTO Yes Unit Building City Yes BuildingBuilding City PLUTO Yes Building Building City 24.5M 41 Yes BuildingBuilding City No Building Building City 6084 55 Yes Building DiscreteRooftop Area City 15.9K 39 Yes Building Building City — — Yes BuildingBuilding City — — Yes Building Building City 34.3K 37 Yes BuildingBuilding City  2.76M 15 Yes Floor Floor City 28.8K 67 Yes BuildingBuilding City 38.2K 25 Yes Building Building City 28.7K 35 Yes FloorFloor City  3.71M 60 Yes Floor Floor City  1.76M 96 Yes Floor Floor City53.4K 36 Yes Building Building City  2.18M 18 Yes Floor Floor City 22.1K19 Yes Building Building City — — Yes Building Building City 66.3K 10Yes Unit Building City  1.03M 8 Yes Building Building City  127K 25 YesBuilding Building City PLUTO Yes Building Building City PLUTO YesBuilding Building City 15.2M 14 Yes Unit Floor City 41.1M 11 Yes UnitFloor City  3.44M 14 Yes Unit Building City  400K 26 Yes BuildingBuilding City 61.7K 19 Yes Floor Building City 29.3K 49 Yes DiscreteDiscrete Rooftop Area City   1.9M 20 Yes Building Building City  2.22M15 Yes Building Building City  6.17M 41 Yes Building Building City 77.8K21 Yes Floor Floor City Yes Floor Floor City Yes Floor Floor City YesFloor Floor City Yes Floor Floor City Yes Floor Floor City Yes FloorFloor City  5.01M 19 No Geographic Geographic Region Region City  6.98M35 Yes Building Building City Yes Building Building City PLUTO YesBuilding Building City Yes Building Building City Yes Building BuildingCity Yes Building Building City Yes Building Building City Yes BuildingBuilding City Yes Unit Floor City  9.85M 40 Yes Building Building CityYes Building Building City Yes Building Building City 2731 20 YesBuilding Building City Yes Unit Floor City  123K 13 Yes BuildingBuilding City Yes Unit Building City Yes Unit Building City 22.1K 61 YesBuilding Building City No Geographic Geographic Region Region City NoGeographic Geographic Region Region City 63.9K 167 Yes Building DiscreteFloor Level City 37.8K 80 Yes Building Discrete Floor Level City  323K21 Yes Building Discrete Floor Level City Yes Building Building City6241 22 Yes Building Discrete Rooftop Area City PLUTO Yes BuildingGeographic Region City PLUTO Yes Building Geographic Region City PLUTOYes Building Geographic Region City PLUTO Yes Building Geographic RegionCity PLUTO Yes Building Geographic Region City PLUTO Yes BuildingGeographic Region City No Line Vector Line Vector City No GeolocatedGeolocated Model Model State Yes Floor Building State Yes Floor BuildingPropSee No Geolocated Geolocated Model Model PropSee No GeolocatedGeolocated Model Model PropSee Yes Unit Unit PropSee Yes Floor FloorPrivate Yes Unit Unit Private No Geolocated Geolocated Model ModelPublic Yes Building Building Public No Geographic Geographic RegionRegion

indicates data missing or illegible when filed

APPENDIX 2 APPENDIX 2 Roles Example Use Case Aerial PhotographerCreating property marketing material using mesh instead of hiringaircraft Appraiser Market research, analytics Architect New developmentpresentation Bank Analyst Find assessment comparables BuildingMechanical Contractors Customer prospecting Building OperationsContractors Customer prospecting City Permit Officer Look for violationsCMBS Analyst Asset Information, portfolio analysis, risk analysisDeveloper Investor presentations, compettivie product analysis EMSFloorplan data Exterior Curtain Wall Contractors Façade inspectionFilmmakers Using mesh and data for cinematic scenes Foreign BuyerUnderstand local neighbourhood, market analysis, target prospectHotellier Competitive survey HVAC Industry Asset tracking, create targetlist of likely purchase Institutional Investor Analyst Market research,rollup of common ownership, risk analysis Institutional InvestorPrincipal Corporate communications, assessment of concentration riskInsurance Adjuster Risk analysis Insurance Inspector FDNY data MezzLender Asset Information, compare asset performance Mortgage Broker Findmortgage documents, track loan maturities Office Investment Sales BrokerExplain market trends, illustrate sales history, value comparison OfficeLeasing Broker Virtually tour space for lease, review alternativesOffice Tenant Space options in the market Parking/Health Club/CaféOperators Comparing operating costs, compare pedestrian traffic countsPrivate Equity Analyst RE portfolio analysis, review concentration riskPrivate Security NYPD data Property Assessor Find property data,comparative analytics Property Manager Business data, charting leaseexirations Property Tax Analyst Comparative analytics Public EquityAnalyst Research Public Investor REIT analysis Real Estate BrokeaageMarketing Presentations, creation of target prospecting lists RealEstate Brokerage Research Presentations, rollup of submarket statisticsResi Buyer Research property history, review market pricing averagesResi Renter View orientation, survey available inventory ResidentialCondo Broker Examine transaction data Residential Rental Broker Massmarket exposure Retail Tenant Demographic site selection SurveyorConfirm information Telecom Operators Roof radio antennae positions UserBuyer Comply with business needs Utility Operator Con Ed network dataVideo Game Developer Using customized reality mesh and highlightingsystem for video game

1.-20. (canceled)
 21. A system to create and display a user controllablethree dimensional interactive reality-based geospatial coordinate-basedreality mesh visualization of a geographic area with buildings and otherstructures, said visualization further including depictions based oncalculated financial determinations related to said buildings overlaidover said geographic area with a processor driven system; said systemcomprising: a server-based processor; at least one repository with atleast text and metadata corresponding to at least some images; at leastone database comprising financial property data; a graphical userinterface (GUI); and a control technology engine for controllingvisualization appearing on said GUI; said processor configured to:recognize selection of a selected geographic area for visualization;identify in said at least one repository text and associated metadatarepresenting the selected geographic area and its environs, as well asrepresenting buildings in said selected geographic area and itsenvirons, including three-dimensional building internal infrastructure,separate living areas, contents, and external structures of eachbuilding in said geographic area, including their spatial locationswithin said geographic area as well as financial property dataassociated with one or more buildings in said geographic area and itsenvirons; curate said text and associated metadata so as to formulatesaid reality mesh visualization; curate said financial property data atleast for associating with individual properties in said reality mesh;populate a data file with said curated text and associated metadata,together with said financial property data, wherein said metadatacharacterizes specific building structural elements beyond aesthetics,and arranged in fields; populate a pick list in said GUI with at least aplurality of said fields for selection, said fields including at leastfinancial parameters based on said financial property data; upon receiptof selection of one or more fields and a selected geographic area, insaid GUI, using the text and associated metadata associated with saidselection of one or more fields, formulate a selectable and scalablevirtual display as a visualized reality mesh of said selected geographicarea, visualized through rendering of geospatial coordinates using aGeographic Information System (GIS), and including one or more overlaysfor selected fields, said overlays organized based on calculated rangesof values for financial parameters and adjusting said overlays based onsaid organization; and afford a user in control of said GUI theopportunity to adjust said visualized reality mesh for geography orfields; wherein said financial parameters are calculated on a per livingunit basis and are based on at least one of recent sales or rentals; adetermined adjustment for internal infrastructure, contents, andexternal structures; tax data; calculated adjustments in value based ondimensional differences; and structural comparisons with similar unitsin the same and other buildings within and outside of said geographicarea.
 22. The system of claim 21, wherein the resolution of said realitymesh is at 2 cm or better.
 23. The system of claim 21, wherein saidoverlays include at least one of shading or shadowing with intensitybased on determined ranges.
 24. The system of claim 21 wherein saidoverlays are color coded based on determined ranges.
 25. The system ofclaim 21, wherein said at least one database is on-goingly populatedwith data from a plurality of sources in communication with saidprocessor.
 26. The system of claim 25, wherein said processor analyzessaid source data, compares said source data to existing data in said atleast one database, performs an error correction function, and populatessaid at least one database to correct identified errors.
 27. The systemof claim 21, wherein said processor regularly polls data sources andcorrespondingly updates said database with newly available financialdata.
 28. The system of claim 27, wherein the step of curating financialproperty data is repeated upon receipt of said newly available financialdata and said visualizations are updated accordingly.
 29. The system ofclaim 21, wherein said financial parameters are further calculated basedon a comparison to other properties in other nearby geographic areas andadjusted based on precise locations in a building and in a geographicarea.
 30. A method for a processor to formulate an executable data file,executable for formulating a multi-dimensional, interactive,visualization on a graphical user interface (GUI) said visualizationincluding overlays coded based on financial ranges, said visualizationformed using curated geospatial coordinates, with orientation andcontent adjustable based upon user input, with a processor drivensystem; said system comprising a data repository comprising at leasttext and metadata corresponding to images, at least one databasecomprising financial property data, a GUI, and a control technologyengine for controlling said GUI; comprising the steps of: identifying insaid at least one database text and related metadata representing aselected three-dimensional geographic area including properties with oneor more units for display as well as buildings and environs, includingthe three-dimensional building internal infrastructure, contents, andexternal structures of each building in said geographic area, includingsaid buildings' spatial locations within said geographic area, as wellas financial data associated with one or more buildings in saidgeographic area and its environs, where said financial data includesrecent sales and rental data; curating said text and related metadata soas to formulate said reality mesh visualization; curating said financialproperty data at least for associating with properties in said realitymesh; populating a data file with said curated text and related metadataregarding legal properties, where said text and related metadatacorresponding to specific detail regarding structural and contentelements beyond aesthetics, and arranged in fields; selecting all fieldsin said at least one database related to said geographic area and itsenvirons for delivery to an executable file; forming an executable filestructured to provide a display to a user based upon said user device;wherein upon execution of said executable file a user may select one ormore fields in said GUI and said file is configured to present avisualized augmented reality mesh in the GUI display visualized throughrendering of geospatial coordinates using a Geographic InformationSystem (GIS) of the selected geography with one or more overlays forselected fields including at least one field related to a calculatedanticipated value for one or more properties in said geographic area andenvirons, said overlays coded based on numerical values in said fields;wherein said anticipated value is calculated based on a combination ofrecent sales or rentals; tax data; dimensional differences; structuralcomparisons with similar units in the same and other buildings withinand outside of said geographic area; and wherein said one or moreoverlays include visualizations based on said calculated anticipatedvalues.
 31. The method of claim 30, wherein said at least one databaseis on-goingly populated with data from a plurality of sources incommunication with said processor.
 32. The method of claim 31, whereinsaid processor is configured to analyze source data, compares saidsource data to existing data in said at least one database, to preforman error correction function, and repopulate and reconfigure said atleast one database based on error correction.
 33. The method of claim30, wherein said coding results in differences in at least one ofshading, shadowing, or color.
 34. The method of claim 30, wherein saidat least one database includes one or more fields detailing fixtures byproperty unit.
 35. A method for a processor to form a color-codedvisualization of a geographic location including one or more calculatedvalues for one or more properties in said geographic location, saidcolor coding based on received data stored in at least one database andcalculations based on said stored data, said data collected on-goinglyfrom at least public sources; said received data being limited to textand metadata; said processor being a part of a system comprising atleast one database, a graphical user interface (GUI), and a controltechnology engine for controlling said GUI; comprising the steps of:selecting a geographic area for display; identifying in said at leastone database fields and content representing a geographic location andits environs as well as buildings and their environs, including thethree-dimensional building internal infrastructure, contents, andexternal structures of each building in said geographic area, includingtheir spatial locations within said geographic area, as well asfinancial data associated with one or more buildings in said geographicarea and its environs, including recent sales and rental data; curatingsaid text and associated metadata so as to formulate said reality meshvisualization; curating said financial property data at least forassociating with properties in said reality mesh; forming a data fileusing said curated text and associated metadata for populating a GUIdisplay, said GUI display including said buildings and environs;populating a pick list in said GUI with fields of identified content forselection; upon selection of one or more fields, determining rangeswithin each field of data for color-coded display; displaying in saidGUI a selectable and scalable geospatial coordinate rendering in areality mesh of the selected geographic location with one or moreoverlays for selected fields, said overlays color coded based oncalculated numerical values in said fields; and affording a user incontrol of said GUI the opportunity to adjust said visualized realitymesh for geography and fields; wherein said numerical values arecalculated based on a combination of recent sales or rentals; tax data;dimensional differences; structural comparisons with similar units inthe same and other buildings within and outside of said geographic areawith a determined adjustment for at least one of location, unit views,unit height, altitude, internal infrastructure, contents, or externalstructures, and calculated adjustments in value based on dimensionaldifferences; and wherein said one or more overlays include visualizationbased on said calculated anticipated values.
 36. The method of claim 35,wherein said color-coding is configured to potentially include shading,translucency, and fogginess based on identified property interest. 37.The method of claim 35, wherein said color coding includes shading,translucency, and fogginess based on value and highlighting one or moreparticular areas of interest.
 38. The method of claim 35, wherein saidvisualization includes one or more charts, where said one or more chartsdisplays data based on at least one of size or a function of calculatedvalue.
 39. The method of claim 35, further including the steps ofaccepting a dynamic search parameter from said GUI, analyzing saidparameter relative to stored text and metadata, and altering saidvisualization based on said analysis.
 40. The method of claim 35,wherein said visualization is altered based on at least one of size ofunit or internal infrastructure.